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app.py
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from ultralytics import YOLO
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from PIL import Image
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import gradio as gr
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from huggingface_hub import snapshot_download
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import os
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#public model path location
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MODEL_REPO_ID = "aunghlaing/6319250G"
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#Organizations model path location
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#MODEL_REPO_ID = "ITI107-2024S2/6319250G"
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#load model
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def load_model(repo_id):
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download_dir = snapshot_download(repo_id)
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print(download_dir)
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path = os.path.join(download_dir, "best_int8_openvino_model")
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print(path)
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detection_model = YOLO(path, task='detect')
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return detection_model
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detection_model = load_model(MODEL_REPO_ID)
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#Student ID
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student_info = "Student Id: 6319250G, Name: AHT"
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#prdeict
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def predict(pilimg):
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source = pilimg
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result = detection_model.predict(source, conf=0.5, iou=0.5)
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img_bgr = result[0].plot()
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out_pilimg = Image.fromarray(img_bgr[..., ::-1]) # RGB-order PIL image
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return out_pilimg
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#UI interface
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gr.Markdown("# Mask & Shark Detection (Mask/Shark)")
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gr.Markdown(student_info)
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gr.Interface(fn=predict,
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inputs=gr.Image(type="pil",label="Input"),
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outputs=gr.Image(type="pil",label="Output"),
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title="Mask & Shark Detection (Mask/Shark)",
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description=student_info,
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).launch(share=True)
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