Upload app.py

app.py

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+import numpy as np
+import cv2 as cv
+import gradio as gr
+
+# Filter functions
+def apply_filter(image, filter_type, brightness=0, blur_level=1):
+    if filter_type == "Grayscale":
+        return cv.cvtColor(image, cv.COLOR_BGR2GRAY)
+    elif filter_type == "Blur":
+        blur_value = max(1, 2 * int(blur_level) + 1)
+        return cv.GaussianBlur(image, (blur_value, blur_value), 0)
+    elif filter_type == "Edge Detection":
+        gray_image = cv.cvtColor(image, cv.COLOR_BGR2GRAY)
+        return cv.Canny(gray_image, 100, 200)
+    elif filter_type == "Brightness Increase":
+        hsv = cv.cvtColor(image, cv.COLOR_BGR2HSV)
+        hsv[:, :, 2] = cv.add(hsv[:, :, 2], brightness)
+        return cv.cvtColor(hsv, cv.COLOR_HSV2BGR)
+    elif filter_type == "Sepia":
+        sepia_filter = np.array([[0.272, 0.534, 0.131],
+                                 [0.349, 0.686, 0.168],
+                                 [0.393, 0.769, 0.189]])
+        sepia_image = cv.transform(image, sepia_filter)
+        sepia_image = np.clip(sepia_image, 0, 255).astype(np.uint8)
+        return sepia_image
+    elif filter_type == "Invert Colors":
+        return cv.bitwise_not(image)
+    elif filter_type == "Sharpen":
+        sharpen_filter = np.array([[0, -1, 0], 
+                                   [-1, 5,-1], 
+                                   [0, -1, 0]])
+        return cv.filter2D(image, -1, sharpen_filter)
+    else:
+        return image  # Return original image by default
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown("Upload an image and select a filter to apply.")
+    gr.Markdown('Drop the file..')
+    # Input and Output components
+    image_input = gr.Image(type="numpy", label="Input Image")
+    filter_buttons = gr.Radio(["Grayscale", "Blur", "Edge Detection", "Brightness Increase", "Sepia", "Invert Colors", "Sharpen"],
+                              label="Choose a Filter", interactive=True)
+    brightness_slider = gr.Slider(0, 100, step=1, label="Brightness Level", visible=False)
+    blur_slider = gr.Slider(1, 20, step=1, label="Blur Level", visible=False)
+    image_output = gr.Image(type="numpy", label="Output Image")
+    
+    # Update slider visibility based on filter type
+    def update_visibility(filter_type):
+        return {
+            brightness_slider: gr.update(visible=(filter_type == "Brightness Increase")),
+            blur_slider: gr.update(visible=(filter_type == "Blur")),
+        }
+
+    # Trigger live updates when sliders or filter type change
+    filter_buttons.change(fn=update_visibility, inputs=filter_buttons, outputs=[brightness_slider, blur_slider])
+    filter_buttons.change(fn=apply_filter, inputs=[image_input, filter_buttons, brightness_slider, blur_slider], outputs=image_output)
+    brightness_slider.change(fn=apply_filter, inputs=[image_input, filter_buttons, brightness_slider, blur_slider], outputs=image_output)
+    blur_slider.change(fn=apply_filter, inputs=[image_input, filter_buttons, brightness_slider, blur_slider], outputs=image_output)
+
+if __name__ == "__main__":
+    demo.launch()