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try: |
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import detectron2 |
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except: |
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import os |
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os.system('pip install git+https://github.com/facebookresearch/detectron2.git') |
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import glob |
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import gradio as gr |
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from os.path import basename |
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from predictor import Predictor |
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predictor = Predictor() |
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def predict(model: str, img_path: str, score_min: int): |
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if not model: |
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raise ValueError('モデルが指定されていません') |
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if not img_path: |
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return ValueError('画像が指定されていません') |
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return predictor.predict(model, img_path, score_min) |
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models = [basename(path) for path in glob.glob("models/*")] |
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images = glob.glob("test/*.jpg") |
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demo = gr.Interface( |
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predict, |
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inputs=[ |
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gr.Dropdown(models, label="モデル", value=models[0]), |
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gr.Image(images[0], type='filepath', label="画像", interactive=True), |
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gr.Slider(0, 100, 80, label="確信度下限(%)", info='指定した確信度以上のオブジェクトのみ検出します。'), |
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], |
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outputs=[ |
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gr.Image(label='結果'), |
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gr.Text(label='パイプの数'), |
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], |
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title="パイプ検出デモ", |
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examples=[[models[0], path, 80] for path in images], |
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allow_flagging='never', |
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) |
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demo.launch() |
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