How can I make proper request to server

[Alex-SSK]

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Environment
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1. OS [e.g. Ubuntu 18.04]:
2. Python version [e.g. 3.8]:
3. DeepSparse version or commit hash [e.g. 0.1.0, f7245c8]:
4. ML framework version(s) [e.g. torch 1.7.1]:
5. Other Python package versions [e.g. SparseML, Sparsify, numpy, ONNX]:
6. CPU info - output of deepsparse/src/deepsparse/arch.bin or output of cpu_architecture() as follows:

>>> import deepsparse.cpu
>>> print(deepsparse.cpu.cpu_architecture())

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I want to deploy Yolov8 with DeepSparse Server. How can I properly make a request with images data?

the endpoint I want to use is 'infer'

[mgoin]

Hey @Alex-SSK here is a simple example of how to hit the yolo entrypoint with an image and get bounding boxes back.

import requests
import json

url = 'http://0.0.0.0:5543/v2/models/yolo/infer/from_files'
path = ['lion.jpeg'] # list of images for inference
files = [('request', open(img, 'rb')) for img in path]
resp = requests.post(url=url, files=files)
annotations = json.loads(resp.text) # dictionary of annotation results
bounding_boxes = annotations["boxes"]
labels = annotations["labels"]
print(labels)

If you need a whole example for annotating an image with the boxes, I can share that later, just let me know!