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("
🎨 Image Studio
") 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("ℹī¸ 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="đŸ–ŧī¸ 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)