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import gradio as gr
from PIL import Image
import numpy as np
import yolov5
model = yolov5.load('keremberke/yolov5n-license-plate')
model.conf = 0.25
model.iou = 0.45
def detect(img: Image.Image):
img = img.convert("RGB")
arr = np.array(img)
results = model(arr, size=640)
results.render()
annotated = results.ims[0]
return Image.fromarray(annotated)
demo = gr.Interface(
fn=detect,
inputs=gr.Image(type="pil"),
outputs=gr.Image(type="pil"),
title="🔍 Detector de Matrículas",
description="Sube una imagen y detecto matrículas usando YOLOv5n."
)
if __name__ == "__main__":
demo.launch()
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