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| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| from datetime import datetime | |
| import random | |
| #----------Start of theme---------- | |
| theme = gr.themes.Soft( | |
| primary_hue="zinc", | |
| secondary_hue="stone", | |
| font=[gr.themes.GoogleFont('Kavivanar'), gr.themes.GoogleFont('Kavivanar'), 'system-ui', 'sans-serif'], | |
| font_mono=[gr.themes.GoogleFont('Source Code Pro'), gr.themes.GoogleFont('Inconsolata'), gr.themes.GoogleFont('Inconsolata'), 'monospace'], | |
| ).set( | |
| body_background_fill='*primary_100', | |
| body_text_color='secondary_600', | |
| body_text_color_subdued='*primary_500', | |
| body_text_weight='500', | |
| background_fill_primary='*primary_100', | |
| background_fill_secondary='*secondary_200', | |
| color_accent='*primary_300', | |
| border_color_accent_subdued='*primary_400', | |
| border_color_primary='*primary_400', | |
| block_background_fill='*primary_300', | |
| block_border_width='*panel_border_width', | |
| block_info_text_color='*primary_700', | |
| block_info_text_size='*text_md', | |
| panel_background_fill='*primary_200', | |
| accordion_text_color='*primary_600', | |
| table_text_color='*primary_600', | |
| input_background_fill='*primary_50', | |
| input_background_fill_focus='*primary_100', | |
| button_primary_background_fill='*primary_500', | |
| button_primary_background_fill_hover='*primary_400', | |
| button_primary_text_color='*primary_50', | |
| button_primary_text_color_hover='*primary_100', | |
| button_cancel_background_fill='*primary_500', | |
| button_cancel_background_fill_hover='*primary_400' | |
| ) | |
| #----------End of theme---------- | |
| def flip_image(x): | |
| return np.fliplr(x) | |
| def basic_filter(image, filter_type): | |
| """Apply basic image filters""" | |
| if filter_type == "Gray Toning": | |
| 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": | |
| # Improved 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 == "Burn it": | |
| return cv2.GaussianBlur(image, (15, 15), 0) | |
| def classic_filter(image, filter_type): | |
| """Classical display filters""" | |
| if filter_type == "Charcoal Effect": | |
| 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 == "Embossing": | |
| 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] | |
| piksel_size = 20 | |
| small = cv2.resize(image, (w//piksel_size, h//piksel_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): | |
| """Apply 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 == "Time Stamp": | |
| 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": | |
| # Improved 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 # saturation increase | |
| return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) | |
| def atmospheric_filters(image, filter_type): | |
| """atmospheric filters""" | |
| if filter_type == "Autumn": | |
| # Genhanced 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 temperature | |
| hsv = cv2.cvtColor(autumn, cv2.COLOR_BGR2HSV) | |
| hsv[:,:,0] = hsv[:,:,0]*0.8 # Shift to orange/yellow tones | |
| hsv[:,:,1] = hsv[:,:,1]*1.2 # Increase saturation | |
| return cv2.cvtColor(hsv, cv2.COLOR_HSV2BGR) | |
| elif filter_type == "Nostalgia": | |
| # Improved nostalgia effect | |
| # Reduce contrast and add yellowish tone | |
| 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] | |
| ])) | |
| # Darkening effect in corners | |
| 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 == "Increase Brightness": | |
| # Improved brightness boost | |
| hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV) | |
| # Increase brightness | |
| hsv[:,:,2] = cv2.convertScaleAbs(hsv[:,:,2], alpha=1.2, beta=30) | |
| # Also increase the contrast slightly | |
| 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_filter_list = ["Gray Toning", "Sepia", "X-ray", "Burn it"] | |
| classic_filter_list = ["Charcoal Effect", "Sharpen", "Embossing", "Edge Detection"] | |
| creative_filters_list = ["Rainbow", "Night Vision"] | |
| special_effects_list = ["Matrix Effect", "Wave Effect", "Time Stamp", "Glitch Effect"] | |
| artistic_filters_list = ["Pop Art", "Oil Paint", "Cartoon"] | |
| atmospheric_filters_list = ["Autumn", "Increase Brightness"] | |
| if filter_type in basic_filter_list: | |
| output = basic_filter(image, filter_type) | |
| elif filter_type in classic_filter_list: | |
| output = classic_filter(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 | |
| css = """ | |
| #app-container { | |
| max-width: 1200px; | |
| margin-left: auto; | |
| margin-right: auto; | |
| } | |
| """ | |
| # Gradio interface | |
| with gr.Blocks(theme=theme, css=css) as app: | |
| gr.HTML("<center><h6>🎨 Image Studio</h6></center>") | |
| with gr.Tab("Text to Image"): | |
| #gr.load("models/digiplay/AnalogMadness-realistic-model-v7") | |
| gr.load("models/XLabs-AI/flux-RealismLora") | |
| with gr.Tab("Flip Image"): | |
| with gr.Row(): | |
| image_input = gr.Image(type="numpy", label="Upload Image") | |
| image_output = gr.Image(format="png") | |
| with gr.Row(): | |
| image_button = gr.Button("Run", variant='primary') | |
| image_button.click(flip_image, inputs=image_input, outputs=image_output) | |
| with gr.Tab("Image Filters"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| image_input = gr.Image(type="numpy", label="Upload Image") | |
| with gr.Accordion("ℹ️ Filter Categories", open=True): | |
| filter_type = gr.Dropdown( | |
| [ | |
| # Basic Filters | |
| "Gray Toning", "Sepia", "X-ray", "Burn it", | |
| # Classic Filter | |
| "Charcoal Effect", "Sharpen", "Embossing", "Edge Detection", | |
| # Creative Filters | |
| "Rainbow", "Night Vision", | |
| # Special Effects | |
| "Matrix Effect", "Wave Effect", "Time Stamp", "Glitch Effect", | |
| # Artistic Filters | |
| "Pop Art", "Oil Paint", "Cartoon", | |
| # Atmospheric Filters | |
| "Autumn", "Increase Brightness" | |
| ], | |
| label="🎭 Select Filter", | |
| info="Choose the effect you want" | |
| ) | |
| submit_button = gr.Button("✨ Apply Filter", variant="primary") | |
| with gr.Column(): | |
| image_output = gr.Image(label="🖼️ Filtered Image") | |
| submit_button.click( | |
| image_processing, | |
| inputs=[image_input, filter_type], | |
| outputs=image_output | |
| ) | |
| with gr.Tab("Image Upscaler"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| def upscale_image(input_image, radio_input): | |
| upscale_factor = radio_input | |
| output_image = cv2.resize(input_image, None, fx = upscale_factor, fy = upscale_factor, interpolation = cv2.INTER_CUBIC) | |
| return output_image | |
| radio_input = gr.Radio(label="Upscale Levels", choices=[2, 4, 6, 8, 10], value=2) | |
| iface = gr.Interface(fn=upscale_image, inputs = [gr.Image(label="Input Image", interactive=True), radio_input], outputs = gr.Image(label="Upscaled Image", format="png"), title="Image Upscaler") | |
| app.launch(share=True) | |