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47 lines
1023 B
Python
47 lines
1023 B
Python
from pydantic import BaseModel
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from fastapi import FastAPI
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from .object_detection import object_detection
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from .image_classifier import image_classifier
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from tf2_yolov4.anchors import YOLOV4_ANCHORS
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from tf2_yolov4.model import YOLOv4
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HEIGHT, WIDTH = (640, 960)
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# Warm up model
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image_classifier.warm_up()
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app = FastAPI()
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class TagImagePayload(BaseModel):
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thumbnail_path: str
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@app.post("/tagImage")
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async def post_root(payload: TagImagePayload):
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image_path = payload.thumbnail_path
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if image_path[0] == '.':
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image_path = image_path[2:]
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return image_classifier.classify_image(image_path=image_path)
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@app.get("/")
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async def test():
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object_detection.run_detection()
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# image = tf.io.read_file("./app/cars.jpg")
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# image = tf.image.decode_image(image)
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# image = tf.image.resize(image, (HEIGHT, WIDTH))
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# images = tf.expand_dims(image, axis=0) / 255.0
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# model = YOLOv4(
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# (HEIGHT, WIDTH, 3),
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# 80,
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# YOLOV4_ANCHORS,
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# "darknet",
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# )
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