Update app.py

app.py

@@ -1,36 +1,31 @@
-import spaces
 import base64
-import cv2
 import numpy as np
+import cv2
 import gradio as gr
 from PIL import Image
 from io import BytesIO
 
-@spaces.GPU
 def crop_face(base64_image):
     try:
-        # Decode the base64 image
+        # Decode the base64 image to an OpenCV format
         img_data = base64.b64decode(base64_image)
         np_arr = np.frombuffer(img_data, np.uint8)
         image = cv2.imdecode(np_arr, cv2.IMREAD_COLOR)
         
         if image is None:
-            return "Could not decode the image or no data in buffer"
-    
+            return "Image decoding failed. Check the input format."
+
         # Load the pre-trained face detector
         face_cascade = cv2.CascadeClassifier(cv2.data.haarcascades + 'haarcascade_frontalface_default.xml')
 
-        # Convert the image to grayscale
+        # Convert the image to grayscale for face detection
         gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
-
-        # Detect faces in the image
         faces = face_cascade.detectMultiScale(gray, scaleFactor=1.1, minNeighbors=5, minSize=(30, 30))
 
-        # If no faces are detected, return message
         if len(faces) == 0:
-            return "No faces found"
+            return "No faces detected in the image."
 
-        # Crop the first face found
+        # Crop the first detected face
         x, y, w, h = faces[0]
         face_crop = image[y:y+h, x:x+w]
 
@@ -44,21 +39,18 @@ def crop_face(base64_image):
         return f"An error occurred: {str(e)}"
 
 def image_to_base64(image):
-    # Convert PIL Image to bytes
-    buffered = io.BytesIO()
+    buffered = BytesIO()
     image.save(buffered, format="JPEG")
-    # Encode bytes to Base64 string
     img_str = base64.b64encode(buffered.getvalue()).decode()
     return img_str
 
-
-# Define the Gradio interface using the updated syntax
+# Define the Gradio interfaces
 base64_converter_interface = gr.Interface(
     fn=image_to_base64, 
     inputs=gr.Image(type="pil"), 
     outputs=gr.Textbox(),
     title="Image to Base64 Encoder",
-    description="Upload an image and convert it to a Base64 encoded string."
+    description="Upload an image to convert it to a base64 encoded string."
 )
 
 face_crop_interface = gr.Interface(
@@ -70,4 +62,4 @@ face_crop_interface = gr.Interface(
 )
 
 if __name__ == "__main__":
-    gr.TabbedInterface([base64_converter_interface, face_crop_interface], ["Convert to Base64","Crop Face"]).launch()
+    gr.TabbedInterface([base64_converter_interface, face_crop_interface], ["Convert to Base64", "Crop Face"]).launch(share=True)