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| from flask import Flask, request, jsonify | |
| from transformers import pipeline | |
| from PIL import Image | |
| import requests | |
| import logging | |
| import torch | |
| from transformers import pipeline | |
| print("Loading model...") | |
| #torch.backends.cuda.matmul.allow_tf32 = True | |
| #torch.backends.cudnn.allow_tf32 = True | |
| pipe = pipeline("image-classification", model="/checkpoint-600") | |
| print("Starting webapp...") | |
| app = Flask(__name__) | |
| log = logging.getLogger('werkzeug') | |
| log.disabled = True | |
| app.logger.disabled = True | |
| print("Ready") | |
| def classify_image(): | |
| global pipe | |
| url = request.args.get('url') | |
| if url is None: | |
| return jsonify(error="Url is required", url=None, label=None) | |
| image = Image.open(requests.get(url, stream=True).raw) | |
| output = pipe(images=[image]) | |
| return jsonify(url=url, result=output[0]) |