Create app.py

app.py

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+from google.colab import drive
+from google.colab.patches import cv2_imshow
+import cv2
+import numpy as np
+import gradio as gr
+
+def detect_sky(image_path):
+
+  img = cv2.imread(image_path)
+
+  hsv_img = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
+
+  h, s, v = cv2.split(hsv_img)
+  v = cv2.equalizeHist(v)
+  mer_img = cv2.merge((h, s, v))
+
+  iLow = np.array([100, 43, 46])
+  iHigh = np.array([124, 255, 255])
+
+  rng_img = cv2.inRange(mer_img, iLow, iHigh)
+
+  kernel = cv2.getStructuringElement(cv2.MORPH_ELLIPSE, (10, 10))
+  erode_img = cv2.erode(rng_img, kernel)
+  dlt_img = cv2.dilate(erode_img, kernel)
+
+  ret, mask = cv2.threshold(dlt_img, 150, 255, cv2.THRESH_BINARY)
+  notmask = cv2.bitwise_not(mask)
+  frontpic = cv2.bitwise_and(img, img, mask=notmask)
+   
+  # Convert the image to RGB format (Gradio expects RGB)
+  result_rgb = cv2.cvtColor(frontpic, cv2.COLOR_BGR2RGB)
+
+    # Encode the image as bytes
+    #_, result_bytes = cv2.imencode('.png', result_rgb)
+    # Convert bytes to a NumPy array
+  return result_rgb
+  
+
+demo = gr.Interface(fn=detect_sky,inputs=gr.Image(type="filepath"),outputs="image")
+
+# Launch the Gradio interface in Colab
+demo.launch()