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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":
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":
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)
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"]
def image_processing(image, filters):
"""Main image processing function"""
if image is None:
return None
image = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
for filter_type in filters:
if filter_type in basic_filters_list:
image = basic_filters(image, filter_type)
elif filter_type in classic_filters_list:
image = classic_filters(image, filter_type)
elif filter_type in creative_filters_list:
image = creative_filters(image, filter_type)
elif filter_type in special_effects_list:
image = special_effects(image, filter_type)
elif filter_type in artistic_filters_list:
image = artistic_filters(image, filter_type)
elif filter_type in atmospheric_filters_list:
image = atmospheric_filters(image, filter_type)
return cv2.cvtColor(image, cv2.COLOR_BGR2RGB) if len(image.shape) == 3 else image
with gr.Blocks(theme=gr.themes.Monochrome()) as app:
gr.Markdown("# 🎨 Image Filter Studio")
with gr.Row():
with gr.Column():
image_input = gr.Image(type="numpy", label="📸 Upload Photo")
with gr.Accordion("ℹ️ Filter Categories", open=True):
filters = gr.CheckboxGroup(
[
"Grayscale", "Sepia", "X-Ray", "Blur",
"Pencil Sketch", "Sharpen", "Emboss", "Edge Detection",
"Pixel Art", "Mosaic Effect", "Rainbow", "Night Vision",
"Matrix Effect", "Wave Effect", "Timestamp", "Glitch Effect",
"Pop Art", "Oil Paint", "Cartoon",
"Autumn", "Nostalgia", "Brightness Increase"
],
label="🎭 Choose Filter(s)",
info="Select multiple effect to apply"
)
submit_button = gr.Button("✨ Apply Filter(s)", variant="primary")
with gr.Column():
image_output = gr.Image(label="🖼️ Filtered Photo")
submit_button.click(
image_processing,
inputs=[image_input, filters],
outputs=image_output
)
app.launch(share=True)
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