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- import requests
- import json
- import io
- import torch
- im, cl, id, pos = torch.load('data/p3ch15/cls_val_example.pt')
- meta = io.StringIO(json.dumps({'shape': list(im.shape)}))
- data = io.BytesIO(bytearray(im.numpy()))
- r = requests.post('http://localhost:8000/predict',
- files={'meta': meta, 'blob' : data})
- response = json.loads(r.content)
- print("Model predicted probability of being maignant:", response['prob_malignant'])
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