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""" |
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Run a Flask REST API exposing one or more YOLOv5s models |
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""" |
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import argparse |
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import io |
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import torch |
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from flask import Flask, request |
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from PIL import Image |
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app = Flask(__name__) |
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models = {} |
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DETECTION_URL = '/v1/object-detection/<model>' |
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@app.route(DETECTION_URL, methods=['POST']) |
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def predict(model): |
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if request.method != 'POST': |
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return |
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if request.files.get('image'): |
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im_file = request.files['image'] |
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im_bytes = im_file.read() |
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im = Image.open(io.BytesIO(im_bytes)) |
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if model in models: |
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results = models[model](im, size=640) |
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return results.pandas().xyxy[0].to_json(orient='records') |
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if __name__ == '__main__': |
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parser = argparse.ArgumentParser(description='Flask API exposing YOLOv5 model') |
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parser.add_argument('--port', default=5000, type=int, help='port number') |
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parser.add_argument('--model', nargs='+', default=['yolov5s'], help='model(s) to run, i.e. --model yolov5n yolov5s') |
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opt = parser.parse_args() |
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for m in opt.model: |
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models[m] = torch.hub.load('ultralytics/yolov5', m, force_reload=True, skip_validation=True) |
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app.run(host='0.0.0.0', port=opt.port) |
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