Update app.py

app.py

@@ -1,138 +1,134 @@
-import cv2
-import numpy as np
-import gradio as gr
-import random
-
-def apply_cartoon_filter(frame):
-    """Cartoon Filter"""
-    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    gray = cv2.medianBlur(gray, 5)
-    edges = cv2.adaptiveThreshold(gray, 255, 
-                                   cv2.ADAPTIVE_THRESH_MEAN_C, 
-                                   cv2.THRESH_BINARY, 11, 7)
-    color = cv2.bilateralFilter(frame, 9, 300, 300)
-    cartoon = cv2.bitwise_and(color, color, mask=edges)
-    return cartoon
-
-def apply_neon_effect(frame):
-    """Neon Light Filter"""
-    # Intensify colors
-    frame_neon = frame.copy().astype(np.float32)
-    frame_neon = np.clip(frame_neon * 1.5, 0, 255).astype(np.uint8)
-    
-    # Highlight edges
-    edges = cv2.Canny(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY), 100, 200)
-    edges_colored = cv2.applyColorMap(edges, cv2.COLORMAP_JET)
-    
-    # Blend
-    result = cv2.addWeighted(frame_neon, 0.7, edges_colored, 0.3, 0)
-    return result
-
-def apply_pixelate_effect(frame, pixel_size=15):
-    """Pixelate Effect"""
-    h, w = frame.shape[:2]
-    small = cv2.resize(frame, (w//pixel_size, h//pixel_size), interpolation=cv2.INTER_LINEAR)
-    return cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)
-
-def apply_glitch_effect(frame):
-    """Glitch Filter"""
-    glitched = frame.copy()
-    
-    # Randomly shift color channels
-    glitched[:, :, 0] = np.roll(glitched[:, :, 0], random.randint(-50, 50), axis=0)
-    glitched[:, :, 1] = np.roll(glitched[:, :, 1], random.randint(-50, 50), axis=1)
-    
-    # Add noise to random areas
-    noise = np.random.randint(0, 255, frame.shape, dtype=np.uint8)
-    glitched = cv2.addWeighted(glitched, 0.7, noise, 0.3, 0)
-    
-    return glitched
-
-def apply_watercolor_effect(frame):
-    """Watercolor Effect"""
-    # Smooth using bilateral filtering
-    frame_soft = cv2.bilateralFilter(frame, 9, 75, 75)
-    
-    # Highlight edges
-    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
-    edges = cv2.Canny(gray, 100, 200)
-    edges = cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
-    
-    # Blend
-    result = cv2.addWeighted(frame_soft, 0.8, edges, 0.2, 0)
-    return result
-
-def apply_upscale(frame, scale_factor=1.5):
-    """
-    Upscaling Effect
-    
-    Args:
-        frame (numpy.ndarray): Input Image
-        scale_factor (float): Scaling Factor (default 1.5)
-    
-    Returns:
-        numpy.ndarray: Upscaled Image
-    """
-    interpolation_methods = [
-        cv2.INTER_CUBIC,     
-        cv2.INTER_LANCZOS4   
-    ]
-    
-    method = random.choice(interpolation_methods)
-    
-    height, width = frame.shape[:2]
-    new_height = int(height * scale_factor)
-    new_width = int(width * scale_factor)
-    
-    upscaled = cv2.resize(frame, (new_width, new_height), interpolation=method)
-    
-    kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
-    sharpened = cv2.filter2D(upscaled, -1, kernel)
-    
-    return sharpened
-
-def apply_filter(filter_type, input_image=None):
-    if input_image is None:
-        cap = cv2.VideoCapture(0)
-        ret, frame = cap.read()
-        cap.release()
-        if not ret:
-            return "Failed to capture image from webcam"
-    else:
-        frame = input_image
-
-    if filter_type == "Upscale":
-        return apply_upscale(frame)
-    elif filter_type == "Cartoon":
-        return apply_cartoon_filter(frame)
-    elif filter_type == "Neon Light":
-        return apply_neon_effect(frame)
-    elif filter_type == "Pixelate":
-        return apply_pixelate_effect(frame)
-    elif filter_type == "Glitch":
-        return apply_glitch_effect(frame)
-    elif filter_type == "Watercolor":
-        return apply_watercolor_effect(frame)
-
-# Gradio interface
-with gr.Blocks() as demo:
-    gr.Markdown('# <p align="center"> OpenCV Image Effects </p>')
-
-    # Filter options
-    filter_type = gr.Dropdown(
-        label="Select Filter",
-        choices=["Upscale","Cartoon", "Neon Light", "Pixelate", "Glitch", "Watercolor"],
-        value="Upscale"
-    )
-
-    with gr.Row():
-        input_image = gr.Image(label="Upload Image", type="numpy")
-        output_image = gr.Image(label="Filtered Image")
-
-    # Apply filter button
-    apply_button = gr.Button("Apply Filter")
-
-    # Apply filter function on button click
-    apply_button.click(fn=apply_filter, inputs=[filter_type, input_image], outputs=output_image)
-
-demo.launch()
+import cv2
+import numpy as np
+import gradio as gr
+import random
+
+def apply_cartoon_filter(frame):
+    """Cartoon Filter"""
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    gray = cv2.medianBlur(gray, 5)
+    edges = cv2.adaptiveThreshold(gray, 255, 
+                                   cv2.ADAPTIVE_THRESH_MEAN_C, 
+                                   cv2.THRESH_BINARY, 11, 7)
+    color = cv2.bilateralFilter(frame, 9, 300, 300)
+    cartoon = cv2.bitwise_and(color, color, mask=edges)
+    return cartoon
+
+def apply_neon_effect(frame):
+    """Neon Light Filter"""
+    # Intensify colors
+    frame_neon = frame.copy().astype(np.float32)
+    frame_neon = np.clip(frame_neon * 1.5, 0, 255).astype(np.uint8)
+    
+    # Highlight edges
+    edges = cv2.Canny(cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY), 100, 200)
+    edges_colored = cv2.applyColorMap(edges, cv2.COLORMAP_JET)
+    
+    # Blend
+    result = cv2.addWeighted(frame_neon, 0.7, edges_colored, 0.3, 0)
+    return result
+
+def apply_pixelate_effect(frame, pixel_size=15):
+    """Pixelate Effect"""
+    h, w = frame.shape[:2]
+    small = cv2.resize(frame, (w//pixel_size, h//pixel_size), interpolation=cv2.INTER_LINEAR)
+    return cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)
+
+def apply_glitch_effect(frame):
+    """Glitch Filter"""
+    glitched = frame.copy()
+    
+    # Randomly shift color channels
+    glitched[:, :, 0] = np.roll(glitched[:, :, 0], random.randint(-50, 50), axis=0)
+    glitched[:, :, 1] = np.roll(glitched[:, :, 1], random.randint(-50, 50), axis=1)
+    
+    return glitched
+
+def apply_watercolor_effect(frame):
+    """Watercolor Effect"""
+    # Smooth using bilateral filtering
+    frame_soft = cv2.bilateralFilter(frame, 9, 75, 75)
+    
+    # Highlight edges
+    gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+    edges = cv2.Canny(gray, 100, 200)
+    edges = cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
+    
+    # Blend
+    result = cv2.addWeighted(frame_soft, 0.8, edges, 0.2, 0)
+    return result
+
+def apply_upscale(frame, scale_factor=1.5):
+    """
+    Upscaling Effect
+    
+    Args:
+        frame (numpy.ndarray): Input Image
+        scale_factor (float): Scaling Factor (default 1.5)
+    
+    Returns:
+        numpy.ndarray: Upscaled Image
+    """
+    interpolation_methods = [
+        cv2.INTER_CUBIC,     
+        cv2.INTER_LANCZOS4   
+    ]
+    
+    method = random.choice(interpolation_methods)
+    
+    height, width = frame.shape[:2]
+    new_height = int(height * scale_factor)
+    new_width = int(width * scale_factor)
+    
+    upscaled = cv2.resize(frame, (new_width, new_height), interpolation=method)
+    
+    kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
+    sharpened = cv2.filter2D(upscaled, -1, kernel)
+    
+    return sharpened
+
+def apply_filter(filter_type, input_image=None):
+    if input_image is None:
+        cap = cv2.VideoCapture(0)
+        ret, frame = cap.read()
+        cap.release()
+        if not ret:
+            return "Failed to capture image from webcam"
+    else:
+        frame = input_image
+
+    if filter_type == "Upscale":
+        return apply_upscale(frame)
+    elif filter_type == "Cartoon":
+        return apply_cartoon_filter(frame)
+    elif filter_type == "Neon Light":
+        return apply_neon_effect(frame)
+    elif filter_type == "Pixelate":
+        return apply_pixelate_effect(frame)
+    elif filter_type == "Glitch":
+        return apply_glitch_effect(frame)
+    elif filter_type == "Watercolor":
+        return apply_watercolor_effect(frame)
+
+# Gradio interface
+with gr.Blocks() as demo:
+    gr.Markdown('# <p align="center"> OpenCV Image Effects </p>')
+
+    # Filter options
+    filter_type = gr.Dropdown(
+        label="Select Filter",
+        choices=["Upscale","Cartoon", "Neon Light", "Pixelate", "Glitch", "Watercolor"],
+        value="Upscale"
+    )
+
+    with gr.Row():
+        input_image = gr.Image(label="Upload Image", type="numpy")
+        output_image = gr.Image(label="Filtered Image")
+
+    # Apply filter button
+    apply_button = gr.Button("Apply Filter")
+
+    # Apply filter function on button click
+    apply_button.click(fn=apply_filter, inputs=[filter_type, input_image], outputs=output_image)
+
+demo.launch()