Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from PIL import Image
+
+def process_image(image, capture_from_webcam=False):
+    """
+    Process an uploaded or captured image: convert it to grayscale.
+    """
+    if capture_from_webcam:
+        # Decode the webcam image
+        image = cv2.imdecode(np.frombuffer(image.read(), np.uint8), cv2.IMREAD_COLOR)
+    else:
+        # Convert uploaded image (PIL) to OpenCV format
+        image = np.array(image)
+        image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    
+    # Convert the image to grayscale
+    gray_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    
+    # Convert back to RGB for display
+    processed_image = cv2.cvtColor(gray_image, cv2.COLOR_GRAY2RGB)
+    return Image.fromarray(processed_image)
+
+# Create the Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("# Image Capture and Processing App")
+    gr.Markdown("Upload an image or use your webcam to capture one, and convert it to grayscale!")
+
+    # Input section
+    with gr.Row():
+        image_input = gr.Image(source="upload", type="pil", label="Upload Image")
+        webcam_input = gr.Image(source="webcam", type="file", label="Capture from Webcam")
+
+    # Output section
+    output_image = gr.Image(type="pil", label="Processed Image")
+
+    # Button to process the uploaded image
+    process_button_upload = gr.Button("Process Uploaded Image")
+    process_button_webcam = gr.Button("Process Webcam Image")
+
+    # Link buttons to the function
+    process_button_upload.click(process_image, inputs=[image_input, gr.Checkbox(value=False)], outputs=output_image)
+    process_button_webcam.click(process_image, inputs=[webcam_input, gr.Checkbox(value=True)], outputs=output_image)
+
+demo.launch()