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| import urllib.request | |
| import io | |
| import json | |
| from PIL import Image | |
| import numpy as np | |
| img = Image.fromarray(np.random.randint(50, 200, (224, 224), dtype=np.uint8), 'L') | |
| buf = io.BytesIO() | |
| img.save(buf, 'PNG') | |
| img_bytes = buf.getvalue() | |
| boundary = 'boundary123' | |
| header1 = b'--boundary123\r\nContent-Disposition: form-data; name="file"; filename="test.png"\r\nContent-Type: image/png\r\n\r\n' | |
| header2 = b'\r\n--boundary123\r\nContent-Disposition: form-data; name="model_name"\r\n\r\nBaseline\r\n--boundary123--' | |
| body = header1 + img_bytes + header2 | |
| req = urllib.request.Request( | |
| 'http://localhost:8000/classify', | |
| data=body, | |
| headers={'Content-Type': 'multipart/form-data; boundary=boundary123'}, | |
| method='POST' | |
| ) | |
| r = urllib.request.urlopen(req) | |
| print(json.loads(r.read())) | |