Mazaal AI Pretrained models API - 1.0
Pretrained model guide
POSTPredict with emotion-english-distilroberta-base
Emotion detection from text
emotion-english-distilroberta-base
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/76Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "I love this"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/76" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "I love this", "input_type": "text"}}'
GETGet result from emotion-english-distilroberta-base
emotion-english-distilroberta-base
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/76?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "5b149110-792a-49fd-bd01-1d18eab9efd6", "output": { "box": [], "score": [ 0.0013875315198674798, 0.0007134044426493347, 0.0003984911891166121, 0.9845667481422424, 0.003475314239040017, 0.004531430546194315, 0.004927210509777069 ], "output": [ "anger", "disgust", "fear", "joy", "neutral", "sadness", "surprise" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 9143, "executionTime": 781 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/76?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolov8m-blood-cell-detection
Detect blood cells in medical images
yolov8m-blood-cell-detection
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/48Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/48" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov8m-blood-cell-detection
yolov8m-blood-cell-detection
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/48?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "f3a29e59-1dc8-4bf6-bd66-f60790f2fed1", "output": { "box": [ [ 1089, 447, 1201, 542 ], [ 369, 256, 457, 346 ], [ 595, 80, 704, 184 ], [ 39, 130, 137, 241 ], [ 503, 422, 595, 520 ], [ 1033, 264, 1126, 366 ], [ 726, 416, 838, 524 ], [ 733, 117, 833, 223 ], [ 1181, 272, 1276, 373 ], [ 196, 235, 290, 333 ], [ 160, 503, 248, 598 ], [ 649, 199, 746, 320 ], [ 1170, 166, 1263, 253 ], [ 1210, 370, 1280, 467 ], [ 193, 326, 290, 433 ], [ 556, 367, 659, 467 ], [ 274, 424, 369, 515 ], [ 825, 65, 947, 172 ], [ 125, 103, 230, 221 ], [ 1037, 166, 1133, 268 ], [ 559, 252, 668, 378 ], [ 564, 497, 652, 588 ], [ 0, 4, 114, 126 ], [ 70, 587, 156, 683 ], [ 0, 289, 93, 403 ], [ 800, 346, 926, 448 ], [ 879, 153, 989, 271 ], [ 1153, 596, 1261, 700 ], [ 273, 273, 377, 388 ], [ 0, 469, 75, 571 ], [ 1105, 67, 1195, 184 ], [ 334, 348, 457, 471 ], [ 474, 249, 570, 381 ], [ 624, 424, 718, 532 ], [ 955, 212, 1045, 332 ], [ 1119, 221, 1200, 354 ], [ 839, 554, 935, 667 ], [ 585, 567, 696, 685 ], [ 1054, 601, 1163, 718 ], [ 77, 490, 170, 601 ], [ 222, 547, 318, 653 ], [ 941, 7, 1120, 200 ], [ 432, 626, 549, 719 ], [ 414, 37, 526, 163 ], [ 721, 563, 853, 661 ], [ 474, 122, 579, 239 ], [ 1049, 359, 1163, 459 ], [ 293, 1, 418, 90 ], [ 231, 482, 318, 558 ], [ 105, 303, 209, 461 ], [ 1185, 509, 1280, 623 ], [ 347, 640, 438, 719 ], [ 850, 250, 963, 368 ], [ 340, 121, 442, 227 ], [ 620, 1, 732, 84 ], [ 1018, 530, 1137, 612 ], [ 1006, 417, 1095, 550 ], [ 952, 594, 1061, 717 ], [ 424, 186, 509, 311 ], [ 0, 554, 69, 663 ], [ 676, 506, 804, 591 ] ], "score": [ 0.872871994972229, 0.867180585861206, 0.8642299175262451, 0.8602820634841919, 0.8592974543571472, 0.856281578540802, 0.8510521054267883, 0.8506277203559875, 0.8501075506210327, 0.8464404344558716, 0.8387285470962524, 0.8376691341400146, 0.8316717743873596, 0.8265300989151001, 0.8249589204788208, 0.8225315809249878, 0.8137295246124268, 0.8129192590713501, 0.8126491904258728, 0.8092378377914429, 0.8091727495193481, 0.8005761504173279, 0.7955678105354309, 0.7950827479362488, 0.7893306016921997, 0.7881128191947937, 0.7812492847442627, 0.7609593868255615, 0.7547171711921692, 0.7464239597320557, 0.7403414249420166, 0.7346124053001404, 0.7333899140357971, 0.7293029427528381, 0.7264273166656494, 0.716696560382843, 0.7145424485206604, 0.7126410603523254, 0.7122524976730347, 0.7085069417953491, 0.6965492367744446, 0.6923624277114868, 0.6895495653152466, 0.6866249442100525, 0.665054440498352, 0.6540052890777588, 0.6479551792144775, 0.6450642943382263, 0.6444165706634521, 0.5977956652641296, 0.5892926454544067, 0.5767989754676819, 0.5687374472618103, 0.5632655620574951, 0.5394450426101685, 0.5343992114067078, 0.4898230731487274, 0.431794673204422, 0.28870469331741333, 0.26873379945755005, 0.25150763988494873 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1 ] } ] }, "status": "COMPLETED", "delayTime": 134386, "executionTime": 5048 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/48?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolov8s
Object detection (generic)
yolov8s
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/44Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/44" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov8s
yolov8s
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/44?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "6d0ed408-2210-4fea-8744-28c5c2ce57ec", "output": { "box": [ [ 745, 41, 1136, 714 ], [ 133, 200, 1127, 714 ], [ 437, 434, 531, 718 ] ], "score": [ 0.894010603427887, 0.8869999647140503, 0.7403771877288818 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ "person", "person", "tie" ] } ] }, "status": "COMPLETED", "delayTime": 5543, "executionTime": 3206 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/44?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with mdeberta-v3-base-mnli-xnli
Zero-shot classification in multiple language
mDeBERTa-v3-base-mnli-xnli
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/98Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU",
"possible_label": [
"politics",
"economy",
"entertainment",
"environment"
]
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/98" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU", "input_type": "text_tags", "possible_label": ["politics", "economy", "entertainment", "environment"]}}'
GETGet result from mdeberta-v3-base-mnli-xnli
mDeBERTa-v3-base-mnli-xnli
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/98?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "c4334025-1cf5-4965-982c-7b5897a49258", "output": { "box": [], "score": [ 0.9658797979354858, 0.022846905514597893, 0.007333934307098389, 0.003939352463930845 ], "output": [ "politics", "economy", "environment", "entertainment" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 14382, "executionTime": 811 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/98?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with background-remover
Remove portrait background
background-remover
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/149Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/149" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from background-remover
background-remover
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/149?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "bdea0f09-f886-4b2f-b026-888781033ee3", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 22884, "executionTime": 4793 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/149?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with inswapper
Swap face
inswapper
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/150Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/150" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "source_image=@cbimage.png;type=image/png" \
-F "target_image=@cbimage_2.png;type=image/png"GETGet result from inswapper
inswapper
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/150?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "b18ef815-980d-4209-8e11-5c5eb91d3463", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 4371, "executionTime": 9215 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/150?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with segment_anything
Segment Anything Model
segment_anything
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/144Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/144" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
-F "possible_label=camera, hat, skateboard" \
GETGet result from segment_anything
segment_anything
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/144?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "571f3075-c678-4b97-b83f-8cfda64fd252", "output": { "box": [ [ 1, 1, 1, 1 ], [ 2, 2, 2, 2 ] ], "score": [ 0.5, 0.4 ], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 10478, "executionTime": 1786 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/144?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with vilt-b32-finetuned-vqa
Ask questions from an image
vilt-b32-finetuned-vqa
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/20Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/20" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=How many cats are there?" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from vilt-b32-finetuned-vqa
vilt-b32-finetuned-vqa
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/20?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "b4548c7a-daca-4b4d-9c89-d6455abe33de", "output": { "box": [], "score": [], "output": [ "1" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 181788, "executionTime": 1869 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/20?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with suno-ai-bark
Generate voice from text Prompt
suno-ai-bark
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/146Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Hello, my name is Suno. And, uh — and I like pizza. [laughs] But I also have other interests such as playing tic tac toe."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/146" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Hello, my name is Suno. And, uh \u2014 and I like pizza. [laughs] But I also have other interests such as playing tic tac toe.", "input_type": "text"}}'
GETGet result from suno-ai-bark
suno-ai-bark
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/146?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "3bf1bd2a-f7a3-43f3-8c30-227a9835ecc6", "output": { "box": [], "score": [], "output": [ "https://runpod-result.s3.ap-southeast-2.amazonaws.com/suno-ai-bark/eab79e96-5a81-4467-abe4-7b621b082f09.wav?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAXUA7OB55IHIQPVPX%2F20230708%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230708T081057Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=23e5421605e66cc234f8d800258e62f05203e9c5912c75f283f74adaafe8527f" ], "data_type": "audio_s3", "additional": [] }, "status": "COMPLETED", "delayTime": 5888, "executionTime": 21342 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/146?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with paddle_ocr
OCR multilingual
paddle_ocr
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/142Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/142" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from paddle_ocr
paddle_ocr
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/142?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "5f35817d-5202-4170-ba6d-60c829fa0e8e", "output": { "box": [ [ [ 48, 10 ], [ 135, 10 ], [ 135, 28 ], [ 48, 28 ] ], [ [ 128, 13 ], [ 187, 13 ], [ 187, 28 ], [ 128, 28 ] ], [ [ 424, 23 ], [ 656, 19 ], [ 656, 60 ], [ 424, 63 ] ], [ [ 706, 18 ], [ 820, 15 ], [ 821, 57 ], [ 707, 59 ] ], [ [ 157, 28 ], [ 353, 25 ], [ 353, 67 ], [ 157, 70 ] ], [ [ 214, 107 ], [ 255, 107 ], [ 255, 131 ], [ 214, 131 ] ], [ [ 342, 105 ], [ 385, 105 ], [ 385, 128 ], [ 342, 128 ] ], [ [ 400, 106 ], [ 456, 106 ], [ 456, 125 ], [ 400, 125 ] ], [ [ 490, 104 ], [ 530, 104 ], [ 530, 124 ], [ 490, 124 ] ], [ [ 546, 104 ], [ 613, 104 ], [ 613, 122 ], [ 546, 122 ] ], [ [ 620, 103 ], [ 647, 103 ], [ 647, 120 ], [ 620, 120 ] ], [ [ 678, 99 ], [ 738, 99 ], [ 738, 121 ], [ 678, 121 ] ], [ [ 753, 98 ], [ 802, 98 ], [ 802, 117 ], [ 753, 117 ] ], [ [ 805, 99 ], [ 834, 99 ], [ 834, 116 ], [ 805, 116 ] ], [ [ 63, 110 ], [ 108, 110 ], [ 108, 133 ], [ 63, 133 ] ], [ [ 119, 111 ], [ 191, 108 ], [ 191, 130 ], [ 119, 132 ] ], [ [ 268, 109 ], [ 315, 107 ], [ 316, 127 ], [ 269, 129 ] ], [ [ 136, 140 ], [ 210, 138 ], [ 210, 161 ], [ 136, 163 ] ], [ [ 342, 177 ], [ 405, 174 ], [ 406, 196 ], [ 343, 198 ] ], [ [ 422, 175 ], [ 468, 175 ], [ 468, 194 ], [ 422, 194 ] ], [ [ 490, 176 ], [ 551, 176 ], [ 551, 195 ], [ 490, 195 ] ], [ [ 569, 174 ], [ 614, 174 ], [ 614, 193 ], [ 569, 193 ] ], [ [ 679, 170 ], [ 767, 170 ], [ 767, 192 ], [ 679, 192 ] ], [ [ 775, 169 ], [ 809, 169 ], [ 809, 189 ], [ 775, 189 ] ], [ [ 67, 181 ], [ 128, 178 ], [ 129, 201 ], [ 68, 203 ] ], [ [ 145, 182 ], [ 168, 182 ], [ 168, 199 ], [ 145, 199 ] ], [ [ 98, 209 ], [ 168, 207 ], [ 168, 226 ], [ 98, 228 ] ], [ [ 89, 230 ], [ 202, 227 ], [ 202, 248 ], [ 89, 252 ] ], [ [ 344, 240 ], [ 450, 235 ], [ 451, 257 ], [ 345, 261 ] ], [ [ 67, 250 ], [ 109, 250 ], [ 109, 272 ], [ 67, 272 ] ], [ [ 125, 253 ], [ 171, 253 ], [ 171, 268 ], [ 125, 268 ] ], [ [ 463, 296 ], [ 503, 298 ], [ 502, 318 ], [ 462, 315 ] ], [ [ 513, 299 ], [ 545, 299 ], [ 545, 315 ], [ 513, 315 ] ], [ [ 551, 298 ], [ 577, 298 ], [ 577, 315 ], [ 551, 315 ] ], [ [ 70, 342 ], [ 113, 342 ], [ 113, 366 ], [ 70, 366 ] ], [ [ 118, 344 ], [ 164, 344 ], [ 164, 363 ], [ 118, 363 ] ], [ [ 489, 453 ], [ 511, 453 ], [ 511, 470 ], [ 489, 470 ] ], [ [ 516, 452 ], [ 596, 449 ], [ 596, 467 ], [ 516, 469 ] ], [ [ 601, 449 ], [ 672, 447 ], [ 672, 466 ], [ 601, 467 ] ], [ [ 676, 447 ], [ 779, 444 ], [ 779, 465 ], [ 676, 467 ] ], [ [ 785, 444 ], [ 832, 444 ], [ 832, 463 ], [ 785, 463 ] ], [ [ 100, 459 ], [ 345, 453 ], [ 345, 473 ], [ 100, 480 ] ], [ [ 361, 454 ], [ 417, 454 ], [ 417, 472 ], [ 361, 472 ] ], [ [ 424, 454 ], [ 480, 454 ], [ 480, 471 ], [ 424, 471 ] ] ], "score": [ 0.5003881454467773, 0.5121922492980957, 0.8410607576370239, 0.9899370074272156, 0.8803550601005554, 0.8953350782394409, 0.6720705628395081, 0.6410766243934631, 0.9981402158737183, 0.9210060834884644, 0.807456374168396, 0.9914864897727966, 0.8868706822395325, 0.8168870210647583, 0.6707069873809814, 0.9028072357177734, 0.8014258742332458, 0.9442926049232483, 0.8741200566291809, 0.6638820171356201, 0.9892856478691101, 0.9861737489700317, 0.8019046187400818, 0.7293807864189148, 0.9992752075195312, 0.7505812048912048, 0.8969690799713135, 0.6176578998565674, 0.7042061686515808, 0.8038582801818848, 0.5054029226303101, 0.9990898370742798, 0.7303234934806824, 0.5139651298522949, 0.6792560815811157, 0.8540811538696289, 0.7028921842575073, 0.8670097589492798, 0.9807087779045105, 0.9929355978965759, 0.6713438630104065, 0.8086974620819092, 0.6298874616622925, 0.6633933186531067 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "full_data": { "english": { "boxes": [ [ [ 3, 8 ], [ 326, 2 ], [ 326, 27 ], [ 3, 33 ] ], [ [ 426, 26 ], [ 663, 21 ], [ 663, 56 ], [ 426, 60 ] ], [ [ 645, 18 ], [ 819, 18 ], [ 819, 54 ], [ 645, 54 ] ], [ [ 399, 106 ], [ 455, 104 ], [ 456, 123 ], [ 400, 125 ] ], [ [ 490, 103 ], [ 648, 101 ], [ 648, 122 ], [ 490, 124 ] ], [ [ 751, 99 ], [ 833, 97 ], [ 833, 114 ], [ 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[ [ 63, 110 ], [ 108, 110 ], [ 108, 133 ], [ 63, 133 ] ], [ [ 119, 111 ], [ 191, 108 ], [ 191, 130 ], [ 119, 132 ] ], [ [ 268, 109 ], [ 315, 107 ], [ 316, 127 ], [ 269, 129 ] ], [ [ 136, 140 ], [ 210, 138 ], [ 210, 161 ], [ 136, 163 ] ], [ [ 342, 177 ], [ 405, 174 ], [ 406, 196 ], [ 343, 198 ] ], [ [ 422, 175 ], [ 468, 175 ], [ 468, 194 ], [ 422, 194 ] ], [ [ 490, 176 ], [ 551, 176 ], [ 551, 195 ], [ 490, 195 ] ], [ [ 569, 174 ], [ 614, 174 ], [ 614, 193 ], [ 569, 193 ] ], [ [ 679, 170 ], [ 767, 170 ], [ 767, 192 ], [ 679, 192 ] ], [ [ 775, 169 ], [ 809, 169 ], [ 809, 189 ], [ 775, 189 ] ], [ [ 67, 181 ], [ 128, 178 ], [ 129, 201 ], [ 68, 203 ] ], [ [ 145, 182 ], [ 168, 182 ], [ 168, 199 ], [ 145, 199 ] ], [ [ 98, 209 ], [ 168, 207 ], [ 168, 226 ], [ 98, 228 ] ], [ [ 89, 230 ], [ 202, 227 ], [ 202, 248 ], [ 89, 252 ] ], [ [ 344, 240 ], [ 450, 235 ], [ 451, 257 ], [ 345, 261 ] ], [ [ 67, 250 ], [ 109, 250 ], [ 109, 272 ], [ 67, 272 ] ], [ [ 125, 253 ], [ 171, 253 ], [ 171, 268 ], [ 125, 268 ] ], [ [ 463, 296 ], [ 503, 298 ], [ 502, 318 ], [ 462, 315 ] ], [ [ 513, 299 ], [ 545, 299 ], [ 545, 315 ], [ 513, 315 ] ], [ [ 551, 298 ], [ 577, 298 ], [ 577, 315 ], [ 551, 315 ] ], [ [ 70, 342 ], [ 113, 342 ], [ 113, 366 ], [ 70, 366 ] ], [ [ 118, 344 ], [ 164, 344 ], [ 164, 363 ], [ 118, 363 ] ], [ [ 489, 453 ], [ 511, 453 ], [ 511, 470 ], [ 489, 470 ] ], [ [ 516, 452 ], [ 596, 449 ], [ 596, 467 ], [ 516, 469 ] ], [ [ 601, 449 ], [ 672, 447 ], [ 672, 466 ], [ 601, 467 ] ], [ [ 676, 447 ], [ 779, 444 ], [ 779, 465 ], [ 676, 467 ] ], [ [ 785, 444 ], [ 832, 444 ], [ 832, 463 ], [ 785, 463 ] ], [ [ 100, 459 ], [ 345, 453 ], [ 345, 473 ], [ 100, 480 ] ], [ [ 361, 454 ], [ 417, 454 ], [ 417, 472 ], [ 361, 472 ] ], [ [ 424, 454 ], [ 480, 454 ], [ 480, 471 ], [ 424, 471 ] ] ], "image": "image", "texts": [ "Uur'a.", "(", "BOAＲDING", "ＰＡＳＳ", "登机牌", "日期", "船位", "CLAS$", "序号", "SER I AL", "N.", "座位号", "SET", "制山", "軌班", "FEIGHT", "DATE", "2379", "始愛地", "FRuh", "登机口", "GATE", "登却嗣面", "BDT", "目的地", "T0", "富山", "F山ZH皇朝", "身併別D", "姓名", "N山MF", "票号", "T正T", "N0", "票併", "FHRE", "10", "MIINUTES", "BEFORE", "DEPARTURE", "TLHE", "登机口千起丞前10分紳英閉", "G上TES", "CLUS王" ], "scores": [ 0.5003881454467773, 0.5121922492980957, 0.8410607576370239, 0.9899370074272156, 0.8803550601005554, 0.8953350782394409, 0.6720705628395081, 0.6410766243934631, 0.9981402158737183, 0.9210060834884644, 0.807456374168396, 0.9914864897727966, 0.8868706822395325, 0.8168870210647583, 0.6707069873809814, 0.9028072357177734, 0.8014258742332458, 0.9442926049232483, 0.8741200566291809, 0.6638820171356201, 0.9892856478691101, 0.9861737489700317, 0.8019046187400818, 0.7293807864189148, 0.9992752075195312, 0.7505812048912048, 0.8969690799713135, 0.6176578998565674, 0.7042061686515808, 0.8038582801818848, 0.5054029226303101, 0.9990898370742798, 0.7303234934806824, 0.5139651298522949, 0.6792560815811157, 0.8540811538696289, 0.7028921842575073, 0.8670097589492798, 0.9807087779045105, 0.9929355978965759, 0.6713438630104065, 0.8086974620819092, 0.6298874616622925, 0.6633933186531067 ] } } } ] }, "status": "COMPLETED", "delayTime": 12133, "executionTime": 6361 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/142?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with table-transformer-structure-recognition
Recognize the structure of tables in documents
table-transformer-structure-recognition
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/40Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/40" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from table-transformer-structure-recognition
table-transformer-structure-recognition
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/40?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "99cd56cc-873c-471a-b2da-8ab9cae8bf99", "output": { "box": [ [ 15.15, 22.06, 561.27, 205.53 ] ], "score": [ 0.998 ], "output": [ "table" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 7048, "executionTime": 1713 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/40?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with fast-segment-anything
Fast Segment Anything
fast-segment-anything
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/145Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/145" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
-F "possible_label=camera, hat, skateboard" \
GETGet result from fast-segment-anything
fast-segment-anything
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/145?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "571f3075-c678-4b97-b83f-8cfda64fd252", "output": { "box": [ [ 1, 1, 1, 1 ], [ 2, 2, 2, 2 ] ], "score": [ 0.5, 0.4 ], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 10478, "executionTime": 1786 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/145?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolov5m-smoke
Smoke detector
yolov5m-smoke
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/54Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/54" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov5m-smoke
yolov5m-smoke
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/54?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "0280eded-0b6c-4df2-9966-b278b920b29f", "output": { "box": [ [ 10.109434127807617, 0, 507.5537109375, 328 ] ], "score": [ 0.6309745907783508 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ 1 ] } ] }, "status": "COMPLETED", "delayTime": 71544, "executionTime": 604 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/54?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with layoutlm-invoices
Extract information from invoice
layoutlm-invoices
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/24Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/24" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=What is the invoice number?" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from layoutlm-invoices
layoutlm-invoices
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/24?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "dd1bd846-570d-43ac-8614-d7e742bc4dcb", "output": { "box": [], "score": [ 0.9999815225601196 ], "output": [ "us-001" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 369263, "executionTime": 1389 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/24?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with sdxl
Generate images from prompt with SDXL
sdxl
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/190Authorization
Parameters
Request Body
application/json
{
"input": {
"prompt": "An astronaut riding a green horse"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/190" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"prompt": "An astronaut riding a green horse", "input_type": "text"}}'
GETGet result from sdxl
sdxl
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/190?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "87a73c2b-7012-4d72-a1fe-ac843b72e0f8", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 317424, "executionTime": 17288 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/190?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with distilbart-mnli-12-3
Zero-shot text classifier
distilbart-mnli-12-3
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/104Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.",
"multiclass": true,
"possible_label": "mobile, website, billing, account access"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/104" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Last week I upgraded my iOS version and ever since then my phone has been overheating whenever I use your app.", "input_type": "text_tags_multiclass", "multiclass": true, "possible_label": "mobile, website, billing, account access"}}'
GETGet result from distilbart-mnli-12-3
distilbart-mnli-12-3
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/104?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "a8eacf88-0b43-49bc-b030-596c4ad6d1ff", "output": { "box": [], "score": [ 0.7477878928184509, 0.3762211203575134, 0.31071746349334717, 0.22285695374011993 ], "output": [ "mobile", "billing", "account access", "website" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 7687, "executionTime": 736 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/104?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with mistral-7b-instruct
mistral-7b-instruct
mistral-7b-instruct
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/193Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": [
{
"role": "system",
"content": "Be precise and concise."
},
{
"role": "user",
"content": "How many stars are there in our galaxy?"
}
]
}
}Responses
- 200 - Returns output
{ "id": "518bcfc1-5c2e-4105-bf13-1dd94e237719", "output": { "box": [], "score": [], "output": [ "The exact number of stars in our galaxy, the Milky Way, is difficult to determine due to the vastness of space and the fact that we can only see a small fraction of it. However, estimates range from hundreds of billions to over a trillion stars." ], "data_type": "text", "additional": [ { "usage": { "total_tokens": 73, "prompt_tokens": 17, "completion_tokens": 56 } } ] }, "status": "", "delayTime": 0, "executionTime": 0 }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/193" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": [{"role": "system", "content": "Be precise and concise."}, {"role": "user", "content": "How many stars are there in our galaxy?"}]}}'
POSTPredict with controlnet-canny
Generate image with control (Canny)
Controlnet-canny
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/133Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/133" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=bird" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-canny
Controlnet-canny
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/133?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "dbd02f65-944f-44e4-abbe-7fb3af3a11cc", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 21942, "executionTime": 12854 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/133?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with vall-e-x
vall-e-x
vall-e-x
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/151Authorization
Parameters
Request Body
application/json
{
"input": {
"prompt": "Hey, Traveler, Listen to this, This machine has taken my voice, and now it can talk just like me!",
"input_str": "audio",
"transcript": "The examination and testimony of the experts enabled the Commission to conclude that five shots may have been fired,"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/151" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"prompt": "Hey, Traveler, Listen to this, This machine has taken my voice, and now it can talk just like me!", "input_str": "audio", "input_type": "audio", "transcript": "The examination and testimony of the experts enabled the Commission to conclude that five shots may have been fired,"}}'
GETGet result from vall-e-x
vall-e-x
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/151?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "4fabecfe-ef40-4823-95d1-763650c97dc3", "output": { "box": [], "score": [], "output": [ "https://runpod-results.s3.amazonaws.com/suno-ai-bark/vall-e-x/56a2f30f-bd2f-4274-bf38-33e9f0643df1.wav?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIAXUA7OB55IHIQPVPX%2F20230902%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230902T024303Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=8837f3d5ebf62d2c24f31a82dbb66191aa48527ca34532e6e080451f5ace37a3" ], "data_type": "audio_s3", "additional": [] }, "status": "COMPLETED", "delayTime": 13464, "executionTime": 5638 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/151?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with whisper
Speech to text
Whisper
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/4Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "https://audio-samples.github.io/samples/mp3/blizzard_biased/sample-0.mp3"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/4" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "https://audio-samples.github.io/samples/mp3/blizzard_biased/sample-0.mp3", "input_type": "text"}}'
GETGet result from whisper
Whisper
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/4?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "29c60bb3-5f70-42dd-85db-ef4072f7d088-u1", "output": { "box": [], "score": [], "output": [ { "id": 0, "end": 5.76, "seek": 0, "text": " Perhaps he made up to the party afterwards and took her and his heart at end continued.", "start": 0, "tokens": [ 50364, 10517, 415, 1027, 493, 281, 264, 3595, 10543, 293, 1890, 720, 293, 702, 1917, 412, 917, 7014, 13, 50652 ], "avg_logprob": -0.3495705321028426, "temperature": 0, "no_speech_prob": 0.009553784504532814, "compression_ratio": 1.2314814814814814 }, { "id": 1, "end": 9.48, "seek": 0, "text": " It was not theorized, set it over her.", "start": 5.76, "tokens": [ 50652, 467, 390, 406, 27423, 1602, 11, 992, 309, 670, 720, 13, 50838 ], "avg_logprob": -0.3495705321028426, "temperature": 0, "no_speech_prob": 0.009553784504532814, "compression_ratio": 1.2314814814814814 } ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 34166, "executionTime": 3435 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/4?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with bert-base-chinese-ner
Extract entity from text(Chinese)
bert-base-chinese-ner
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/86Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "我叫萨拉，我住在伦敦。"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/86" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "\u6211\u53eb\u8428\u62c9\uff0c\u6211\u4f4f\u5728\u4f26\u6566\u3002", "input_type": "text"}}'
GETGet result from bert-base-chinese-ner
bert-base-chinese-ner
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/86?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "027e65a6-9d35-4eda-860b-90c6b1ff44b8", "output": { "box": [], "score": [ 0.04742075875401497, 0.047555334866046906, 0.03239244222640991, 0.04414321482181549, 0.045149095356464386, 0.04886113479733467, 0.05155876651406288, 0.050095636397600174, 0.02861616015434265, 0.042885009199380875, 0.04037574306130409 ], "output": [ "S-WORK_OF_ART", "S-WORK_OF_ART", "E-DATE", "S-LOC", "S-WORK_OF_ART", "S-WORK_OF_ART", "S-WORK_OF_ART", "S-WORK_OF_ART", "S-DATE", "B-CARDINAL", "S-WORK_OF_ART" ], "data_type": "text", "additional": [ { "end": 1, "word": "我", "start": 0 }, { "end": 2, "word": "叫", "start": 1 }, { "end": 3, "word": "萨", "start": 2 }, { "end": 4, "word": "拉", "start": 3 }, { "end": 5, "word": "，", "start": 4 }, { "end": 6, "word": "我", "start": 5 }, { "end": 7, "word": "住", "start": 6 }, { "end": 8, "word": "在", "start": 7 }, { "end": 9, "word": "伦", "start": 8 }, { "end": 10, "word": "敦", "start": 9 }, { "end": 11, "word": "。", "start": 10 } ] }, "status": "COMPLETED", "delayTime": 7241, "executionTime": 713 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/86?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with esg-bert
Classify text into ESG topic
ESG-BERT
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/78Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "In fiscal year 2019, we reduced our comprehensive carbon footprint for the fourth consecutive year—down 35 percent compared to 2015, when Apple’s carbon emissions peaked, even as net revenue increased by 11 percent over that same period. In the past year, we avoided over 10 million metric tons from our emissions reduction initiatives—like our Supplier Clean Energy Program, which lowered our footprint by 4.4 million metric tons. "
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/78" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "In fiscal year 2019, we reduced our comprehensive carbon footprint for the fourth consecutive year\u2014down 35 percent compared to 2015, when Apple\u2019s carbon emissions peaked, even as net revenue increased by 11 percent over that same period. In the past year, we avoided over 10 million metric tons from our emissions reduction initiatives\u2014like our Supplier Clean Energy Program, which lowered our footprint by 4.4 million metric tons. ", "input_type": "text"}}'
GETGet result from esg-bert
ESG-BERT
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/78?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "1f227963-670c-4edb-b12a-b626efd1d6f1", "output": { "box": [], "score": [ 0.7454295754432678 ], "output": [ "GHG_Emissions" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 6831, "executionTime": 926 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/78?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with vit-gpt2-image-captioning
Generate description from an image
vit-gpt2-image-captioning
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/12Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/12" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from vit-gpt2-image-captioning
vit-gpt2-image-captioning
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/12?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "f0c7a40c-9111-4b22-9240-bebd92f38a9d", "output": { "box": [], "score": [], "output": [ "airplanes parked on the tarmac at an airport" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 10818, "executionTime": 1982 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/12?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with twitter-roberta-base-sentiment-latest
Tweet sentiment analysis
twitter-roberta-base-sentiment-latest
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/72Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Covid cases are increasing fast!"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/72" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Covid cases are increasing fast!", "input_type": "text"}}'
GETGet result from twitter-roberta-base-sentiment-latest
twitter-roberta-base-sentiment-latest
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/72?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "4731d25e-d11f-4ebc-81f0-7a71e984b998", "output": { "box": [], "score": [ 0.723576545715332 ], "output": [ "negative" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 8125, "executionTime": 766 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/72?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with distilbert-base-uncased-finetuned-sst-2-english
Sentiment analysis
distilbert-base-uncased-finetuned-sst-2-english
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/70Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "I like you. I love you"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/70" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "I like you. I love you", "input_type": "text"}}'
GETGet result from distilbert-base-uncased-finetuned-sst-2-english
distilbert-base-uncased-finetuned-sst-2-english
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/70?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "8efb05c6-128b-4162-8eae-cdd6785af5f8", "output": { "box": [], "score": [], "output": [ "LABEL_0" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 21565, "executionTime": 942 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/70?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with maskformer-swin-base-coco
Object detection and instance segmentation
maskformer-swin-base-coco
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/60Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/60" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from maskformer-swin-base-coco
maskformer-swin-base-coco
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/60?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "9d778526-ede4-42a4-ab09-f6c49b97cc54", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 115986, "executionTime": 2378 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/60?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with keyphrase-extraction-kbir-inspec
Extract keyphrases from text
keyphrase-extraction-kbir-inspec
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/88Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document. Thanks to these keyphrases humans can understand the content of a text very quickly and easily without reading it completely. Keyphrase extraction was first done primarily by human annotators, who read the text in detail and then wrote down the most important keyphrases. The disadvantage is that if you work with a lot of documents, this process can take a lot of time. Here is where Artificial Intelligence comes in. Currently, classical machine learning methods, that use statistical and linguistic features, are widely used for the extraction process. Now with deep learning, it is possible to capture the semantic meaning of a text even better than these classical methods. Classical methods look at the frequency, occurrence and order of words in the text, whereas these neural approaches can capture long-term semantic dependencies and context of words in a text."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/88" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Keyphrase extraction is a technique in text analysis where you extract the important keyphrases from a document. Thanks to these keyphrases humans can understand the content of a text very quickly and easily without reading it completely. Keyphrase extraction was first done primarily by human annotators, who read the text in detail and then wrote down the most important keyphrases. The disadvantage is that if you work with a lot of documents, this process can take a lot of time. Here is where Artificial Intelligence comes in. Currently, classical machine learning methods, that use statistical and linguistic features, are widely used for the extraction process. Now with deep learning, it is possible to capture the semantic meaning of a text even better than these classical methods. Classical methods look at the frequency, occurrence and order of words in the text, whereas these neural approaches can capture long-term semantic dependencies and context of words in a text.", "input_type": "text"}}'
GETGet result from keyphrase-extraction-kbir-inspec
keyphrase-extraction-kbir-inspec
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/88?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "2355707d-0b9b-43cf-9c8f-83acc0defc2f", "output": { "box": [], "score": [], "output": [ "Artificial Intelligence", "Keyphrase extraction", "deep learning", "linguistic features", "machine learning", "semantic meaning", "text analysis" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 11391, "executionTime": 1213 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/88?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with dpt-large
Estimate depth from image
dpt-large
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/26Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/26" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from dpt-large
dpt-large
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/26?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "10c77f40-6104-42b9-83f9-9c476651f599", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 9692, "executionTime": 2165 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/26?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with vit-age-classifier
Guess age group of a person
vit-age-classifier
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/30Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/30" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from vit-age-classifier
vit-age-classifier
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/30?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "f4f75c83-c0fe-400e-b471-b6dd87a8758f", "output": { "box": [], "score": [], "output": [ "30-39" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 6944, "executionTime": 1654 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/30?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with layoutlm-document-qa
Ask questions from your image document
layoutlm-document-qa
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/22Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/22" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=What is the purchase amount?" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from layoutlm-document-qa
layoutlm-document-qa
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/22?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "c5afcf29-3ab0-44cb-b05e-65348785e436", "output": { "box": [], "score": [ 0.9998503923416138 ], "output": [ "$1,000,000,000" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 225793, "executionTime": 2340 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/22?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with sdxl-base
None
sdxl-base
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/196Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Astronaut riding a horse"
}
}Responses
- 200 - Returns output
{ "id": "", "output": { "box": [], "score": [], "output": [ "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" ], "data_type": "image_base64", "additional": [] }, "status": "", "delayTime": 0, "executionTime": 0 }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/196" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Astronaut riding a horse"}}'
POSTPredict with trocr-base-handwritten
Handwritten text recognition
trocr-base-handwritten
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/16Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/16" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from trocr-base-handwritten
trocr-base-handwritten
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/16?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "d54436fe-3bf3-4fb8-9a72-4424f589f12e", "output": { "box": [], "score": [], "output": [ "\" Will you pour your own, please, and" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 18060, "executionTime": 2411 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/16?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolos-tiny
Fast object detection
yolos-tiny
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/36Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/36" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolos-tiny
yolos-tiny
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/36?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "6e3616b8-731f-4ec0-a76f-81a034667e15", "output": { "box": [ [ 278.48, 195.16, 360.6, 219.42 ], [ 381.71, 198.08, 465.59, 265.45 ], [ 221.94, 226.58, 235.09, 264.23 ], [ 461.45, 144.41, 639.31, 414.62 ] ], "score": [ 0.982, 0.952, 0.995, 0.99 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ "airplane", "bus", "person", "bus" ] } ] }, "status": "COMPLETED", "delayTime": 54269, "executionTime": 205 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/36?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with toxic-comment-model
Detect toxic comments in text
toxic-comment-model
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/80Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "This is a test text."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/80" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "This is a test text.", "input_type": "text"}}'
GETGet result from toxic-comment-model
toxic-comment-model
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/80?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "199a4630-4702-463f-8fe3-b93c9cd484c7", "output": { "box": [], "score": [ 0.9990898370742798 ], "output": [ "non-toxic" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 6698, "executionTime": 702 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/80?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with owlvit-base-patch32
Ask AI to classify image to categories you defined
owlvit-base-patch32
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/32Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/32" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
-F "possible_label=['a photo of a cat', 'a photo of a dog']" \
GETGet result from owlvit-base-patch32
owlvit-base-patch32
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/32?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "1a63fbea-ed44-409e-8a56-f7b740d0d72d", "output": { "box": [ [ 324.97, 20.44, 640.58, 373.29 ], [ 1.46, 55.26, 315.55, 472.17 ] ], "score": [ 0.707, 0.717 ], "output": [ "a photo of a cat", "a photo of a cat" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 8228, "executionTime": 2311 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/32?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-depth
Generate image with control (Depth)
Controlnet-depth
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/134Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/134" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=Stormtrooper's lecture" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-depth
Controlnet-depth
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/134?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "a9eaa150-1b57-4010-8f99-dea46498fd9a", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 38417, "executionTime": 7856 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/134?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-mlsd
Generate image with control (M-LSD)
Controlnet-mlsd
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/136Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/136" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=room" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-mlsd
Controlnet-mlsd
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/136?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "338e1554-9397-48b9-95b3-dc91b749c1bc", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 11371, "executionTime": 6628 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/136?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with easyocr-model
OCR clean
easyocr-model
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/197Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/197" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "language=en" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from easyocr-model
easyocr-model
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/197?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "22a54d34-ee47-4e9e-a44c-348dddc42681-e1", "output": { "box": [ [ [ 19, 35 ], [ 121, 35 ], [ 121, 79 ], [ 19, 79 ] ], [ [ 161, 39 ], [ 383, 39 ], [ 383, 77 ], [ 161, 77 ] ], [ [ 461, 36 ], [ 1191, 36 ], [ 1191, 81 ], [ 461, 81 ] ], [ [ 19, 86 ], [ 1274, 86 ], [ 1274, 135 ], [ 19, 135 ] ], [ [ 23, 141 ], [ 921, 141 ], [ 921, 185 ], [ 23, 185 ] ], [ [ 937, 141 ], [ 1373, 141 ], [ 1373, 185 ], [ 937, 185 ] ], [ [ 20, 191 ], [ 1234, 191 ], [ 1234, 239 ], [ 20, 239 ] ], [ [ 20, 244 ], [ 1375, 244 ], [ 1375, 287 ], [ 20, 287 ] ], [ [ 21, 299 ], [ 459, 299 ], [ 459, 335 ], [ 21, 335 ] ], [ [ 23, 382 ], [ 1351, 382 ], [ 1351, 425 ], [ 23, 425 ] ], [ [ 21, 432 ], [ 1347, 432 ], [ 1347, 477 ], [ 21, 477 ] ], [ [ 21, 486 ], [ 532, 486 ], [ 532, 530 ], [ 21, 530 ] ], [ [ 19, 565 ], [ 1257, 565 ], [ 1257, 614 ], [ 19, 614 ] ], [ [ 21, 619 ], [ 1366, 619 ], [ 1366, 667 ], [ 21, 667 ] ], [ [ 21, 673 ], [ 1339, 673 ], [ 1339, 717 ], [ 21, 717 ] ], [ [ 18, 724 ], [ 1269, 724 ], [ 1269, 767 ], [ 18, 767 ] ], [ [ 18, 773 ], [ 1368, 773 ], [ 1368, 823 ], [ 18, 823 ] ], [ [ 18, 823 ], [ 920, 823 ], [ 920, 874 ], [ 18, 874 ] ], [ [ 995, 831 ], [ 1363, 831 ], [ 1363, 873 ], [ 995, 873 ] ], [ [ 383.56408368276453, 42.26661757518776 ], [ 457.4207913262161, 36.926793135626625 ], [ 459.43591631723547, 75.73338242481223 ], [ 384.5792086737839, 81.07320686437338 ] ], [ [ 919.5144372945836, 834.286093236459 ], [ 993.4207913262161, 828.9267931356267 ], [ 995.4855627054164, 866.713906763541 ], [ 920.5792086737839, 873.0732068643733 ] ] ], "score": [ 0.9999435957003707, 0.8238194196355783, 0.756580447137365, 0.7443800690886677, 0.8612622701622986, 0.7423349920402619, 0.6844377684766633, 0.9349099736213771, 0.7376112395782498, 0.6828765123346197, 0.8024260374976069, 0.9034096277385537, 0.5469501211828564, 0.7710497775347921, 0.4792564275033408, 0.6142218864122763, 0.6335683537688406, 0.7705991575099215, 0.6640427397319505, 0.9999977350234985, 0.9999983906745911 ], "output": [ "(CNN)", "Phantom limb", "is a common problem for people who undergo", "amputation, and so is the ability to function even with a regular prosthetic, but a", "medical advance that sounds like it comes straight out of", "Star Wars\" is giving at least", "one woman significant relief from that pain: She now has a functioning bionic", "prosthetic hand that can feel some sensations and help her do about 80% of what she", "used to do with both hands:", "While Luke Skywalker's human-like bionic hand is still years away, scientists say they", "are a step closer with this newest prosthetic technique, and doctors hope others will", "soon benefit from this approach:", "Karin, whose full name is not disclosed in the proof of concept study published", "Wednesday in the medical journal Science Robot; had been using a regular prosthetic", "hand for years; but it was hard to control: And as with even the most technologically", "advanced prosthetics on the market; it was uncomfortable and sometimes even", "painful to use. On top of that; the Swedish 50-year-old, who lost her hand in a farming", "accident; had been living with excruciating phantom Iimb", "for more than 20 years:", "pain", "pain" ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 114212, "executionTime": 4924 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/197?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-normal
Generate image with control (Normal Map)
Controlnet-normal
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/137Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/137" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=cute toy" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-normal
Controlnet-normal
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/137?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "fce4ed95-da8b-479a-9758-3abba1cb8950", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 31078, "executionTime": 9338 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/137?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolov8m-table-extraction
Extract tables from documents with high accuracy
yolov8m-table-extraction
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/46Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/46" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov8m-table-extraction
yolov8m-table-extraction
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/46?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "41f508a1-d435-4705-8c96-50d9feab100b", "output": { "box": [ [ 54, 398, 697, 539 ], [ 55, 398, 700, 538 ] ], "score": [ 0.5058751106262207, 0.2670725882053375 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ 0, 1 ] } ] }, "status": "COMPLETED", "delayTime": 207107, "executionTime": 4537 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/46?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-hed
Generate image with control (HED)
Controlnet-hed
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/135Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/135" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=oil painting of handsome old man, masterpiece" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-hed
Controlnet-hed
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/135?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "0af8613e-3fee-4509-8e17-4bc9b5d7f82e", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 20715, "executionTime": 6834 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/135?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolos-small-finetuned-license-plate-detection
Detect license plates in images
yolos-small-finetuned-license-plate-detection
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/42Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/42" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolos-small-finetuned-license-plate-detection
yolos-small-finetuned-license-plate-detection
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/42?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "e4db7d32-ba14-4b14-bbcc-d3badd804e2b", "output": { "box": [ [ 589.14, 390.47, 620.13, 405.3 ], [ 421.03, 249.81, 439.54, 257.1 ], [ 482.19, 350.21, 507.25, 373.14 ] ], "score": [ 0.965, 0.969, 0.966 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ "license-plates", "license-plates", "license-plates" ] } ] }, "status": "COMPLETED", "delayTime": 155714, "executionTime": 1417 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/42?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-scribble
Generate image with control (Scribble)
Controlnet-scribble
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/139Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/139" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=bag" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-scribble
Controlnet-scribble
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/139?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "5d812395-a228-4bce-8270-cb71935227fd", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 16101, "executionTime": 8783 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/139?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-openpose
Generate image with control (HumanPose)
Controlnet-openpose
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/138Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/138" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=chef in the kitchen" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-openpose
Controlnet-openpose
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/138?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "826a3c19-9370-403f-afc1-e0001ea76e5a", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 26011, "executionTime": 8440 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/138?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with bert-zero-shot
Answer question based on the provided context (multilingual support)
bert-zero-shot
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/94Authorization
Parameters
Request Body
application/json
{
"input": {
"prompt": "Who was Jim Henson?",
"input_str": "Jim Henson was a nice puppet"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/94" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"prompt": "Who was Jim Henson?", "input_str": "Jim Henson was a nice puppet", "input_type": "text_prompt"}}'
GETGet result from bert-zero-shot
bert-zero-shot
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/94?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "5073c243-af86-4b2d-b708-1c932c5e4217", "output": { "box": [], "score": [], "output": [ "a nice puppet" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 451204, "executionTime": 1034 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/94?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with xlm-roberta-base-language-detection
Detect the language of text
xlm-roberta-base-language-detection
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/74Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "A new model offers an explanation for how the Galilean satellites formed around the solar system’s largest world. Konstantin Batygin did not set out to solve one of the solar system’s most puzzling mysteries when he went for a run up a hill in Nice, France. Dr. Batygin, a Caltech researcher, best known for his contributions to the search for the solar system’s missing “Planet Nine,” spotted a beer bottle. At a steep, 20 degree grade, he wondered why it wasn’t rolling down the hill. He realized there was a breeze at his back holding the bottle in place. Then he had a thought that would only pop into the mind of a theoretical astrophysicist: “Oh! This is how Europa formed.” Europa is one of Jupiter’s four large Galilean moons. And in a paper published Monday in the Astrophysical Journal, Dr. Batygin and a co-author, Alessandro Morbidelli, a planetary scientist at the Côte d’Azur Observatory in France, present a theory explaining how some moons form around gas giants like Jupiter and Saturn, suggesting that millimeter-sized grains of hail produced during the solar system’s formation became trapped around these massive worlds, taking shape one at a time into the potentially habitable moons we know today."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/74" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "A new model offers an explanation for how the Galilean satellites formed around the solar system\u2019s largest world. Konstantin Batygin did not set out to solve one of the solar system\u2019s most puzzling mysteries when he went for a run up a hill in Nice, France. Dr. Batygin, a Caltech researcher, best known for his contributions to the search for the solar system\u2019s missing \u201cPlanet Nine,\u201d spotted a beer bottle. At a steep, 20 degree grade, he wondered why it wasn\u2019t rolling down the hill. He realized there was a breeze at his back holding the bottle in place. Then he had a thought that would only pop into the mind of a theoretical astrophysicist: \u201cOh! This is how Europa formed.\u201d Europa is one of Jupiter\u2019s four large Galilean moons. And in a paper published Monday in the Astrophysical Journal, Dr. Batygin and a co-author, Alessandro Morbidelli, a planetary scientist at the C\u00f4te d\u2019Azur Observatory in France, present a theory explaining how some moons form around gas giants like Jupiter and Saturn, suggesting that millimeter-sized grains of hail produced during the solar system\u2019s formation became trapped around these massive worlds, taking shape one at a time into the potentially habitable moons we know today.", "input_type": "text"}}'
GETGet result from xlm-roberta-base-language-detection
xlm-roberta-base-language-detection
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/74?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "20338e75-2c12-4ad3-8f79-0d21ca8c5ff3", "output": { "box": [], "score": [ 0.9376141428947449 ], "output": [ "en" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 9613, "executionTime": 731 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/74?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with controlnet-seg
Generate image with control (Seg)
Controlnet-seg
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/140Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/140" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=house" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from controlnet-seg
Controlnet-seg
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/140?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "191c61c8-288a-4334-8890-6a1ce79d0993", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 10559, "executionTime": 6204 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/140?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with yolov5m-aerial-sheep
Count livestock from drone images
yolov5m-aerial-sheep
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/52Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/52" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov5m-aerial-sheep
yolov5m-aerial-sheep
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/52?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "245205a5-c235-4c93-8984-eda8de9a3925", "output": { "box": [ [ 748.1644897460938, 0.98598712682724, 851.4412231445312, 139.43295288085938 ], [ 592.2642211914062, 44.867496490478516, 674.0306396484375, 92.3136215209961 ], [ 144.62445068359375, 90.02764129638672, 265.3022155761719, 243.42520141601562 ], [ 286.8462829589844, 18.296815872192383, 414.011474609375, 124.23201751708984 ], [ 362.40679931640625, 17.72300910949707, 428.2760925292969, 114.29322814941406 ], [ 635.36376953125, 145.09317016601562, 748.7760620117188, 259.65411376953125 ], [ 143.46888732910156, 218.3687286376953, 195.52609252929688, 300.5218505859375 ], [ 643.8408203125, 125.71057891845703, 706.5503540039062, 176.34226989746094 ] ], "score": [ 0.7986444234848022, 0.7087119817733765, 0.6010277271270752, 0.5480892658233643, 0.5478705763816833, 0.5051766037940979, 0.3331335484981537, 0.3020903468132019 ], "output": [ 1, 1, 1, 1, 1, 1, 1, 1 ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 9907, "executionTime": 940 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/52?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with donut-base
Classify documents(in image format)
donut-base
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/18Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/18" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "prompt=What is the invoice number?" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from donut-base
donut-base
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/18?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "5b5e29e2-9777-49a0-99e1-3a9b32c34a4e", "output": { "box": [], "score": [], "output": [ { "answer": "us-001", "question": "What is the invoice number?" } ], "data_type": "image_text", "additional": [] }, "status": "COMPLETED", "delayTime": 166407, "executionTime": 3907 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/18?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with biomedical-ner-all
Recognise biomedical entities
biomedical-ner-all
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/82Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "The patient reported no recurrence of palpitations at follow-up 6 months after the ablation."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/82" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "The patient reported no recurrence of palpitations at follow-up 6 months after the ablation.", "input_type": "text"}}'
GETGet result from biomedical-ner-all
biomedical-ner-all
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/82?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "0bccd462-d36e-4858-a653-e64e62288a08", "output": { "box": [], "score": [ 0.9999310970306396, 0.9063321352005005, 0.9997554421424866, 0.9998670220375061 ], "output": [ "Sign_symptom", "Sign_symptom", "Clinical_event", "Date" ], "data_type": "text", "additional": [ { "end": 41, "word": "pal", "start": 38 }, { "end": 50, "word": "##pitations", "start": 41 }, { "end": 60, "word": "follow", "start": 54 }, { "end": 78, "word": "6 months after", "start": 64 } ] }, "status": "COMPLETED", "delayTime": 233420, "executionTime": 689 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/82?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with nix-tts
Text to Speech
nix-tts
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/126Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Born to multiply, born to gaze into night skies."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/126" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Born to multiply, born to gaze into night skies.", "input_type": "text"}}'
GETGet result from nix-tts
nix-tts
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/126?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "d364a69b-8a17-494a-875d-cc0ab37c66d1", "input": { "input_str": "**When conwoman Melissa Caddick vanished from her luxurious eastern Sydney home in November 2020 - with only her partially decomposed foot found washed up on a beach months later - it set off a frenzy in Australia.** The case blindsided investors, baffled police, and captured the imagination of a nation. ", "input_type": "text" }, "output": { "box": [], "score": [], "output": [ "http://s3.amazonaws.com/runpod-test-524/runpod-tmp/cd9e81bc-7f91-4103-8e3f-01017f414c07.wav?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=AKIATGT26DYU2ECVDXGH%2F20230525%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20230525T050304Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=634846daba96fce5a6755e03c96ad14c29dea0baef9203085d8f3910be202ddd" ], "data_type": "audio_s3", "additional": [] }, "status": "COMPLETED", "delayTime": 4165, "executionTime": 10251 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/126?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with skin-retouch
Beautify the skin of a portrait
skin-retouch
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/148Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/148" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from skin-retouch
skin-retouch
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/148?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "41023c8f-da22-4d09-a1b9-e74c18c82bac", "output": { "box": [], "score": [], "output": [ "image" ], "data_type": "image_base64", "additional": [] }, "status": "COMPLETED", "delayTime": 162632, "executionTime": 6865 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/148?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with bert-base-multilingual-cased-ner-hrl
Recognise entity in multiple languages
bert-base-multilingual-cased-ner-hrl
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/84Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "Nader Jokhadar had given Syria the lead with a well-struck header in the seventh minute."
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/84" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "Nader Jokhadar had given Syria the lead with a well-struck header in the seventh minute.", "input_type": "text"}}'
GETGet result from bert-base-multilingual-cased-ner-hrl
bert-base-multilingual-cased-ner-hrl
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/84?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "7206d52d-3ca2-4601-8ab8-96f8b0ae6e69", "output": { "box": [], "score": [ 0.9997156262397766, 0.9816160202026367, 0.9997740387916565, 0.9998015761375427, 0.9997687935829163, 0.9997319579124451 ], "output": [ "B-PER", "I-PER", "I-PER", "I-PER", "I-PER", "B-LOC" ], "data_type": "text", "additional": [ { "end": 3, "word": "Nad", "start": 0 }, { "end": 5, "word": "##er", "start": 3 }, { "end": 8, "word": "Jo", "start": 6 }, { "end": 11, "word": "##kha", "start": 8 }, { "end": 14, "word": "##dar", "start": 11 }, { "end": 30, "word": "Syria", "start": 25 } ] }, "status": "COMPLETED", "delayTime": 402362, "executionTime": 583 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/84?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with llama-2-70b-chat-hf
huggingface llama-2-70b-chat-hf
llama-2-70b-chat-hf
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/186Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "In a surprising turn of events, "
}
}Responses
- 200 - Returns output
{ "id": "", "output": { "box": [], "score": [], "output": [ "In a surprising turn of events, 20th Century Fox has released a new trailer for Ridley Scott's Alien" ], "data_type": "text", "additional": [] }, "status": "", "delayTime": 0, "executionTime": 0 }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/186" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "In a surprising turn of events, "}}'
POSTPredict with yolov5n-construction-safety
Construction safety
yolov5n-construction-safety
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/50Authorization
Parameters
Request Body
multipart/form-data
Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/50" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-F "image=@test_image.jpeg;type=image/jpeg" \
GETGet result from yolov5n-construction-safety
yolov5n-construction-safety
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/50?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "331c867a-6013-4d53-a8d3-048498e876a6", "output": { "box": [ [ 224.37596130371094, 12.396671295166016, 306.4808349609375, 110.99388885498047 ] ], "score": [ 0.9434449672698975 ], "output": [ "image" ], "data_type": "image_base64", "additional": [ { "labels": [ 4 ] } ] }, "status": "COMPLETED", "delayTime": 144953, "executionTime": 600 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/50?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"
POSTPredict with stable-diffusion-2
Generate images with Stable Diffusion v2
stable-diffusion-2
[POST] https://dev.mazaal.ai/api/sdk/pre-trained-models/8Authorization
Parameters
Request Body
application/json
{
"input": {
"input_str": "highly detailed, HD, 4K, portrait of elon musk, van gogh style"
}
}Responses
- 200 - Returns output
{ "id": "9d21daec-f5fb-4b86-83f8-8b54c480a24b", "status": "IN_QUEUE" }
Request Examples
cURL
curl -X POST "https://dev.mazaal.ai/api/sdk/pre-trained-models/8" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX" \
-d '{"input": {"input_str": "highly detailed, HD, 4K, portrait of elon musk, van gogh style", "input_type": "text"}}'
GETGet result from stable-diffusion-2
stable-diffusion-2
[GET] https://dev.mazaal.ai/api/sdk/pre-trained-models/output/8?outId={process_id}Authorization
Parameters
- process_id (query) - Process ID returned from a POST request.
Request Body
Responses
- 200 - Returns output
{ "id": "a3568540-3451-4cc5-acb1-f2dbbeb8ba5c-u1", "output": { "box": [], "score": [], "output": [ "https://14068d66ba387efac9ce5e4b1741bcf2.r2.cloudflarestorage.com/ai-api/10-23/a3568540-3451-4cc5-acb1-f2dbbeb8ba5c-u1/64f1a360.png?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=16b502c87564788383d52ec498a61a24%2F20231018%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Date=20231018T083204Z&X-Amz-Expires=604800&X-Amz-SignedHeaders=host&X-Amz-Signature=63864e04a3ce3531343cc75dd75da5d4492ebd065010cb5b1416d99628fb2bed" ], "data_type": "text", "additional": [] }, "status": "COMPLETED", "delayTime": 8420, "executionTime": 32609 }
Request Examples
cURL
curl -X GET "https://dev.mazaal.ai/api/sdk/pre-trained-models/output/8?outId={process_id}" \
-H "Authorization: Bearer mz-XXXXXXXXXXXX"