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Varun
Refactor object detection in app.py to use YOLOv8 model from Hugging Face, removing DiffusionPipeline. Update requirements.txt to include ultralytics and numpy, and adjust Gradio output type.
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import gradio as gr | |
from ultralytics import YOLO | |
# Load YOLOv8 model from Hugging Face | |
model = YOLO( | |
"https://huggingface.co/Lookingsoft-team/object_detection/resolve/main/yolov8n.pt" | |
) | |
def detect_objects(image): | |
results = model(image) | |
annotated_image = results[0].plot() # Draw bounding boxes | |
return annotated_image | |
demo = gr.Interface( | |
fn=detect_objects, | |
inputs=gr.Image(type="pil"), | |
outputs=gr.Image(type="numpy"), | |
title="Object Detection", | |
description="Upload an image for object detection!", | |
) | |
if __name__ == "__main__": | |
demo.launch() | |