aunghlaiingtun commited on
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8a8c8c6
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1 Parent(s): 7357461

my frist app

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best_int8_openvino_model/best.bin ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:667c192bfb8a38ad7a5fafe62868185de02720203ac793ec36a5cd2d4201c9dc
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+ size 26059692
best_int8_openvino_model/best.xml ADDED
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best_int8_openvino_model/metadata.yaml ADDED
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+ description: Ultralytics best model trained on datasets/data.yaml
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+ author: Ultralytics
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+ date: '2024-12-24T19:25:07.780379'
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+ version: 8.3.54
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+ license: AGPL-3.0 License (https://ultralytics.com/license)
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+ docs: https://docs.ultralytics.com
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+ stride: 32
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+ task: detect
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+ batch: 1
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+ imgsz:
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+ - 640
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+ - 640
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+ names:
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+ 0: mask
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+ 1: shark
twoobjectdetect.py ADDED
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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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+
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+ #model_path = "/Users/markk/Downloads/best_int8_openvino_model"
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+ #model_path1 = "C:\Users\aungh\Downloads\6319250G\best_int8_openvino_model"
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+
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+ # Define the path to the YOLOv8 mo
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+ model_path = "./best_int8_openvino_model"
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+
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+ #Organizations model path location
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+ MODEL_REPO_ID = "ITI107-2024S2/6319250G"
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+
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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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+
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+ detection_model = load_model(MODEL_REPO_ID)
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+
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+ #Student ID
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+ student_info = "Student Id: 6319250G, Name: AUNG HTUN"
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+
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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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+
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+ #UI interface
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+ gr.Markdown("# Two Object Detection (Shark/Mask)")
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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="Two Object Detection (Shark/Mask)",
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+ description=student_info,
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+ ).launch(share=True)