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Helmet-Detect-model/.gitattributes

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Helmet-Detect-model/README.md

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+---
+title: Helmet Detect Model
+emoji: ⚡
+colorFrom: indigo
+colorTo: gray
+sdk: gradio
+sdk_version: 5.0.1
+app_file: app.py
+pinned: false
+license: apache-2.0
+short_description: this for helmet detect for the safety of the driver
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

Helmet-Detect-model/app.py

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+import gradio as gr
+from ultralytics import YOLO
+from PIL import Image
+import os
+
+
+
+# Load the trained YOLOv8 model
+model = YOLO("best.pt")
+
+# Define the prediction function
+def predict(image):
+    results = model(image)  # Run YOLOv8 model on the uploaded image
+    results_img = results[0].plot()  # Get image with bounding boxes
+    return Image.fromarray(results_img)
+
+# Get example images from the images folder
+def get_example_images():
+    examples = []
+    image_folder = "images"
+    for filename in os.listdir(image_folder):
+        if filename.lower().endswith(('.png', '.jpg', '.jpeg')):
+            examples.append(os.path.join(image_folder, filename))
+    return examples
+
+# Create Gradio interface
+interface = gr.Interface(
+    fn=predict, 
+    inputs=gr.Image(type="pil"), 
+    outputs=gr.Image(type="pil"),
+    title="Helmet Detection with YOLO",
+    description="Upload an image to detect helmets.",
+    examples=get_example_images()
+)
+
+# Launch the interface
+interface.launch(share=True)

Helmet-Detect-model/best.pt

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+size 46779223