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Update app.py
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app.py
CHANGED
@@ -1,33 +1,40 @@
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import gradio as gr
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import PIL.Image as Image
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from ultralytics import ASSETS, YOLO
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model = YOLO("https://huggingface.co/spaces/gpbhupinder/test/blob/main/model_-%2023%20june%202024%2019_22.pt")
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def predict_image(img):
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"""Predicts objects in an image using a YOLOv8 model."""
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results = model.predict(
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source=img,
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show_labels=True,
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show_conf=True,
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imgsz=640,
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)
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-
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for r in results:
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im_array = r.plot()
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im = Image.fromarray(im_array[..., ::-1])
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return im
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iface = gr.Interface(
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fn=predict_image,
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inputs=[
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gr.Image(type="pil", label="Upload Image"),
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],
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outputs=
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gr.Image(type="pil", label="Result"),
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gr.Textbox(label="Predictions")
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],
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title="GP Wolf Classifier",
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description="Upload images for inference.",
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examples=[
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import gradio as gr
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import PIL.Image as Image
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from ultralytics import ASSETS, YOLO
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model = YOLO("https://huggingface.co/spaces/gpbhupinder/test/blob/main/model_-%2023%20june%202024%2019_22.pt")
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+
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def predict_image(img):
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"""Predicts objects in an image using a YOLOv8 model."""
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results = model.predict(
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source=img,
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+
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show_labels=True,
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show_conf=True,
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imgsz=640,
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+
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)
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+
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for r in results:
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im_array = r.plot()
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im = Image.fromarray(im_array[..., ::-1])
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return im
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iface = gr.Interface(
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fn=predict_image,
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inputs=[
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gr.Image(type="pil", label="Upload Image"),
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# gr.Slider(minimum=0, maximum=1, value=0.25, label="Confidence threshold"),
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# gr.Slider(minimum=0, maximum=1, value=0.45, label="IoU threshold"),
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],
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outputs=gr.Image(type="pil", label="Result"),
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title="GP Wolf Classifier",
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description="Upload images for inference.",
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examples=[
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