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app (3).py

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+import gradio as gr
+import cv2
+import numpy as np
+from ultralytics import YOLO
+
+model = YOLO('best (7).pt')
+
+def predict_image(img): 
+        
+  model = YOLO('best (7).pt')
+  result = model.predict(img,conf=0.97)
+  res_plotted = result[0].plot()
+  #cv2.imshow( res_plotted)
+  return res_plotted
+
+
+
+image = gr.inputs.Image()
+
+label = gr.outputs.Label('ok')
+gr.Interface(fn=predict_image, inputs=image, outputs=image).launch(debug='True')

requirements (2).txt

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+ultralytics
+opencv-python
+numpy
+gradio