Create app.py

app.py

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+import gradio as gr
+import cv2
+import numpy as np
+from datetime import datetime
+import random
+
+def basic_filters(image, filter_type):
+    """Applies basic image filters"""
+    if filter_type == "Grayscale":
+        return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+    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]
+        ])
+        return cv2.transform(image, sepia_filter)
+    elif filter_type == "X-Ray":
+        # Enhanced X-ray effect
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        inverted = cv2.bitwise_not(gray)
+        # Increase contrast
+        clahe = cv2.createCLAHE(clipLimit=3.0, tileGridSize=(8,8))
+        enhanced = clahe.apply(inverted)
+        # Sharpen
+        kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
+        sharpened = cv2.filter2D(enhanced, -1, kernel)
+        return cv2.cvtColor(sharpened, cv2.COLOR_GRAY2BGR)
+    elif filter_type == "Blur":
+        return cv2.GaussianBlur(image, (15, 15), 0)
+
+def classic_filters(image, filter_type):
+    """Classic image filters"""
+    if filter_type == "Pencil Sketch":
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        inverted = cv2.bitwise_not(gray)
+        blurred = cv2.GaussianBlur(inverted, (21, 21), 0)
+        sketch = cv2.divide(gray, cv2.subtract(255, blurred), scale=256)
+        return cv2.cvtColor(sketch, cv2.COLOR_GRAY2BGR)
+    
+    elif filter_type == "Sharpen":
+        kernel = np.array([[-1,-1,-1], [-1,9,-1], [-1,-1,-1]])
+        return cv2.filter2D(image, -1, kernel)
+    
+    elif filter_type == "Emboss":
+        kernel = np.array([[0,-1,-1], [1,0,-1], [1,1,0]])
+        gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
+        emboss = cv2.filter2D(gray, -1, kernel) + 128
+        return cv2.cvtColor(emboss, cv2.COLOR_GRAY2BGR)
+    
+    elif filter_type == "Edge Detection":
+        edges = cv2.Canny(image, 100, 200)
+        return cv2.cvtColor(edges, cv2.COLOR_GRAY2BGR)
+
+def creative_filters(image, filter_type):
+    """Creative and unusual image filters"""
+    if filter_type == "Pixel Art":
+        h, w = image.shape[:2]
+        pixel_size = 20
+        small = cv2.resize(image, (w//pixel_size, h//pixel_size))
+        return cv2.resize(small, (w, h), interpolation=cv2.INTER_NEAREST)
+    
+    elif filter_type == "Mosaic Effect":
+        h, w = image.shape[:2]
+        mosaic_size = 30
+        for i in range(0, h, mosaic_size):
+            for j in range(0, w, mosaic_size):
+                roi = image[i:i+mosaic_size, j:j+mosaic_size]
+                if roi.size > 0:
+                    color = np.mean(roi, axis=(0,1))
+                    image[i:i+mosaic_size, j:j+mosaic_size] = color
+        return image
+    
+    elif filter_type == "Rainbow":
+        hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+        h, w = image.shape[:2]
+        for i in range(h):
+            hsv[i, :, 0] = (hsv[i, :, 0] + i % 180).astype(np.uint8)
+        return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+    
+    elif filter_type == "Night Vision":
+        green_image = image.copy()
+        green_image[:,:,0] = 0  # Blue channel
+        green_image[:,:,2] = 0  # Red channel
+        return cv2.addWeighted(green_image, 1.5, np.zeros(image.shape, image.dtype), 0, -50)
+
+def special_effects(image, filter_type):
+    """Applies special effects"""
+    if filter_type == "Matrix Effect":
+        green_matrix = np.zeros_like(image)
+        green_matrix[:,:,1] = image[:,:,1]  # Only green channel
+        random_brightness = np.random.randint(0, 255, size=image.shape[:2])
+        green_matrix[:,:,1] = np.minimum(green_matrix[:,:,1] + random_brightness, 255)
+        return green_matrix
+    
+    elif filter_type == "Wave Effect":
+        rows, cols = image.shape[:2]
+        img_output = np.zeros(image.shape, dtype=image.dtype)
+        
+        for i in range(rows):
+            for j in range(cols):
+                offset_x = int(25.0 * np.sin(2 * 3.14 * i / 180))
+                offset_y = int(25.0 * np.cos(2 * 3.14 * j / 180))
+                if i+offset_x < rows and j+offset_y < cols:
+                    img_output[i,j] = image[(i+offset_x)%rows,(j+offset_y)%cols]
+                else:
+                    img_output[i,j] = 0
+        return img_output
+    
+    elif filter_type == "Timestamp":
+        output = image.copy()
+        timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+        font = cv2.FONT_HERSHEY_SIMPLEX
+        cv2.putText(output, timestamp, (10, 30), font, 1, (255, 255, 255), 2)
+        return output
+    
+    elif filter_type == "Glitch Effect":
+        glitch = image.copy()
+        h, w = image.shape[:2]
+        for _ in range(10):
+            x1 = random.randint(0, w-50)
+            y1 = random.randint(0, h-50)
+            x2 = random.randint(x1, min(x1+50, w))
+            y2 = random.randint(y1, min(y1+50, h))
+            glitch[y1:y2, x1:x2] = np.roll(glitch[y1:y2, x1:x2], 
+                                          random.randint(-20, 20), 
+                                          axis=random.randint(0, 1))
+        return glitch
+
+def artistic_filters(image, filter_type):
+    """Applies artistic image filters"""
+    if filter_type == "Pop Art":
+        img_small = cv2.resize(image, None, fx=0.5, fy=0.5)
+        img_color = cv2.resize(img_small, (image.shape[1], image.shape[0]))
+        for _ in range(2):
+            img_color = cv2.bilateralFilter(img_color, 9, 300, 300)
+        hsv = cv2.cvtColor(img_color, cv2.COLOR_BGR2HSV)
+        hsv[:,:,1] = hsv[:,:,1]*1.5
+        return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+    
+    elif filter_type == "Oil Paint":
+        ret = np.float32(image.copy())
+        ret = cv2.bilateralFilter(ret, 9, 75, 75)
+        ret = cv2.detailEnhance(ret, sigma_s=15, sigma_r=0.15)
+        ret = cv2.edgePreservingFilter(ret, flags=1, sigma_s=60, sigma_r=0.4)
+        return np.uint8(ret)
+    
+    elif filter_type == "Cartoon":
+        # Enhanced cartoon effect
+        color = image.copy()
+        gray = cv2.cvtColor(color, cv2.COLOR_BGR2GRAY)
+        gray = cv2.medianBlur(gray, 5)
+        edges = cv2.adaptiveThreshold(gray, 255, cv2.ADAPTIVE_THRESH_MEAN_C, cv2.THRESH_BINARY, 9, 9)
+        color = cv2.bilateralFilter(color, 9, 300, 300)
+        cartoon = cv2.bitwise_and(color, color, mask=edges)
+        # Increase color saturation
+        hsv = cv2.cvtColor(cartoon, cv2.COLOR_BGR2HSV)
+        hsv[:,:,1] = hsv[:,:,1]*1.4  # Increase saturation
+        return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+
+def atmospheric_filters(image, filter_type):
+    """Applies atmospheric filters"""
+    if filter_type == "Autumn":
+        # Enhanced autumn effect
+        autumn_filter = np.array([
+            [0.393, 0.769, 0.189],
+            [0.349, 0.686, 0.168],
+            [0.272, 0.534, 0.131]
+        ])
+        autumn = cv2.transform(image, autumn_filter)
+        # Increase color warmth
+        hsv = cv2.cvtColor(autumn, cv2.COLOR_BGR2HSV)
+        hsv[:,:,0] = hsv[:,:,0]*0.8  # Shift towards orange/yellow tones
+        hsv[:,:,1] = hsv[:,:,1]*1.2  # Increase saturation
+        return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR)
+    
+    elif filter_type == "Nostalgia":
+        # Enhanced nostalgia effect
+        # Reduce contrast and add a yellowish tint
+        image = cv2.convertScaleAbs(image, alpha=0.9, beta=10)
+        sepia = cv2.transform(image, np.array([
+            [0.393, 0.769, 0.189],
+            [0.349, 0.686, 0.168],
+            [0.272, 0.534, 0.131]
+        ]))
+        # Add vignette effect
+        h, w = image.shape[:2]
+        kernel = np.zeros((h, w))
+        center = (h//2, w//2)
+        for i in range(h):
+            for j in range(w):
+                dist = np.sqrt((i-center[0])**2 + (j-center[1])**2)
+                kernel[i,j] = 1 - min(1, dist/(np.sqrt(h**2 + w**2)/2))
+        kernel = np.dstack([kernel]*3)
+        return cv2.multiply(sepia, kernel).astype(np.uint8)
+    
+    elif filter_type == "Brightness Increase":
+        # Enhanced brightness increase
+        hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
+        # Increase brightness
+        hsv[:,:,2] = cv2.convertScaleAbs(hsv[:,:,2], alpha=1.2, beta=30)
+        # Slightly increase contrast
+        return cv2.convertScaleAbs(cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR), alpha=1.1, beta=0)
+
+def image_processing(image, filter_type):
+    """Main image processing function"""
+    if image is None:
+        return None
+    
+    image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
+    
+    # Process by filter categories
+    basic_filters_list = ["Grayscale", "Sepia", "X-Ray", "Blur"]
+    classic_filters_list = ["Pencil Sketch", "Sharpen", "Emboss", "Edge Detection"]
+    creative_filters_list = ["Pixel Art", "Mosaic Effect", "Rainbow", "Night Vision"]
+    special_effects_list = ["Matrix Effect", "Wave Effect", "Timestamp", "Glitch Effect"]
+    artistic_filters_list = ["Pop Art", "Oil Paint", "Cartoon"]
+    atmospheric_filters_list = ["Autumn", "Nostalgia", "Brightness Increase"]
+    
+    if filter_type in basic_filters_list:
+        output = basic_filters(image, filter_type)
+    elif filter_type in classic_filters_list:
+        output = classic_filters(image, filter_type)
+    elif filter_type in creative_filters_list:
+        output = creative_filters(image, filter_type)
+    elif filter_type in special_effects_list:
+        output = special_effects(image, filter_type)
+    elif filter_type in artistic_filters_list:
+        output = artistic_filters(image, filter_type)
+    elif filter_type in atmospheric_filters_list:
+        output = atmospheric_filters(image, filter_type)
+    else:
+        output = image
+        
+    return cv2.cvtColor(output, cv2.COLOR_BGR2RGB) if len(output.shape) == 3 else output
+
+# Gradio interface
+with gr.Blocks(theme=gr.themes.Monochrome()) as app:
+    gr.Markdown("# 🎨 Super and Unusual Image Filtering Studio")
+    gr.Markdown("### 🌈 Add magical touches to your photos!")
+    
+    with gr.Row():
+        with gr.Column():
+            image_input = gr.Image(type="numpy", label="📸 Upload Photo")
+            with gr.Accordion("ℹ️ Filter Categories", open=True):
+                filter_type = gr.Radio(
+                    [
+                        # Basic Filters
+                        "Grayscale", "Sepia", "X-Ray", "Blur",
+                        # Classic Filters 
+                        "Pencil Sketch", "Sharpen", "Emboss", "Edge Detection",                       
+                        # Creative Filters
+                        "Pixel Art", "Mosaic Effect", "Rainbow", "Night Vision",
+                        # Special Effects
+                        "Matrix Effect", "Wave Effect", "Timestamp", "Glitch Effect",
+                        # Artistic Filters
+                        "Pop Art", "Oil Paint", "Cartoon",
+                        # Atmospheric Filters
+                        "Autumn", "Nostalgia", "Brightness Increase"
+                    ],
+                    label="🎭 Choose Filter",
+                    info="Select your magical effect"
+                )
+            submit_button = gr.Button("✨ Apply Filter", variant="primary")
+            
+        with gr.Column():
+            image_output = gr.Image(label="🖼️ Filtered Photo")
+    
+    with gr.Accordion("📝 Filter Descriptions", open=False):
+        gr.Markdown("""
+        ### 🎨 Filter Categories and Effects
+        
+        #### 📊 Basic Filters
+        - **Grayscale**: Converts the image to black-and-white tones, giving it a classic look
+        - **Sepia**: Adds warm brown tones, creating an old-photo feel
+        - **X-Ray**: Adds inverse lighting to create an X-ray scan effect
+        - **Blur**: Applies a soft blur to the image, reducing detail.                
+        
+        #### 🖼️ Classic Filters List
+        - **Pencil Sketch**: Makes the image look like a pencil drawing
+        - **Sharpen**: Enhances details in the image
+        - **Emboss**: Adds an embossing effect with depth
+        - **Edge Detection**: Highlights the edge lines in the image          
+        
+        #### 🎮 Creative Filters
+        - **Pixel Art**: Breaks the image into small squares in a retro pixel style
+        - **Mosaic Effect**: Divides the image into small mosaic pieces
+        - **Rainbow**: Adds colorful rainbow effects to the image
+        - **Night Vision**: Simulates a night-vision device effect
+        
+        #### 🎬 Special Effects
+        - **Matrix Effect**: Matrix movie effect
+        - **Wave Effect**: Adds a wavy distortion, creating a ripple sensation
+        - **Timestamp**: Adds the date and time the photo was taken, giving a nostalgic touch
+        - **Glitch Effect**: Adds digital distortions for a retro-style glitch effect
+        
+        #### 🎭 Artistic Filters
+        - **Pop Art**: Creates an iconic pop-art effect in the style of Andy Warhol, with bright colors and contrasts
+        - **Oil Paint**: Simulates brush strokes, giving the image an oil painting look
+        - **Texture Effect**: Adds surface texture for a tactile depth and art piece feel
+        """)
+    
+    submit_button.click(
+        image_processing,
+        inputs=[image_input, filter_type],
+        outputs=image_output
+    )
+
+app.launch(share=True)