Flask REST API Example (#2732)
* add files * Update README.md * Update README.md * Update restapi.py pretrained=True and model.eval() are used by default when loading a model now, so no need to call them manually. * PEP8 reformat * PEP8 reformat Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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"""
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Run a rest API exposing the yolov5s object detection model
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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 PIL import Image
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from flask import Flask, request
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app = Flask(__name__)
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DETECTION_URL = "/v1/object-detection/yolov5s"
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@app.route(DETECTION_URL, methods=["POST"])
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def predict():
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if not request.method == "POST":
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return
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if request.files.get("image"):
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image_file = request.files["image"]
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image_bytes = image_file.read()
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img = Image.open(io.BytesIO(image_bytes))
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results = model(img, size=640)
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data = results.pandas().xyxy[0].to_json(orient="records")
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return data
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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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args = parser.parse_args()
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model = torch.hub.load("ultralytics/yolov5", "yolov5s", force_reload=True).autoshape() # force_reload to recache
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app.run(host="0.0.0.0", port=args.port) # debug=True causes Restarting with stat
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