Image_Studio / app.py
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import gradio as gr
import cv2
import numpy as np
import os
from datetime import datetime
import random
from transformers import pipeline
#----------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----------
API_TOKEN = os.getenv("HF_READ_TOKEN")
headers = {"Authorization": f"Bearer {API_TOKEN}"}
timeout = 100
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.HTML("<center><b>Flux</b></center>")
#gr.load("models/XLabs-AI/flux-RealismLora")
#gr.load("models/digiplay/AnalogMadness-realistic-model-v7")
gr.load("stabilityai/stable-diffusion-3-medium-diffusers")
gr.load("models/dvyio/flux-lora-film-noir")
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
)
app.launch(share=True)