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import numpy as np
from cvzone.SelfiSegmentationModule import SelfiSegmentation
import os
import time
import gradio as gr
segmen = SelfiSegmentation()
def save_image_to_desktop(image):
desktop_path = os.path.expanduser("~/Desktop")
project_folder = os.path.join(desktop_path, "project")
os.makedirs(project_folder, exist_ok=True)
timestamp = int(time.time())
file_name = f"image_{timestamp}.jpg"
file_path = os.path.join(project_folder, file_name)
cv2.imwrite(file_path, image)
return file_path
def apply_sepia_filter(frame):
sepia_kernel = np.array([[0.131, 0.534, 0.272],
[0.168, 0.686, 0.349],
[0.189, 0.769, 0.393]])
sepia_image = cv2.transform(frame, sepia_kernel)
return np.clip(sepia_image, 0, 255).astype(np.uint8)
def apply_emboss_filter(image):
emboss_kernel = np.array([[-2, -1, 0], [-1, 1, 1], [0, 1, 2]])
emboss_image = cv2.filter2D(image, -1, emboss_kernel)
return np.clip(emboss_image, 0, 255).astype(np.uint8)
def pixelate(image):
pixel_size = 10
height, width = image.shape[:2]
temp_image = cv2.resize(image, (width // pixel_size, height // pixel_size), interpolation=cv2.INTER_NEAREST)
return cv2.resize(temp_image, (width, height), interpolation=cv2.INTER_NEAREST)
def apply_edge_enhance(image):
enhanced_edge_kernel = np.array([[-1, -1, -1], [-1, 10, -1], [-1, -1, -1]])
enhanced_edge_image = cv2.filter2D(image, -1, enhanced_edge_kernel)
return np.clip(enhanced_edge_image, 0, 255).astype(np.uint8)
def brightness_control(image, value):
img_float = np.float32(image)
img_float += value
img_float = np.clip(img_float, 0, 255)
brightened_image = np.uint8(img_float)
return brightened_image
def final(option1,option2, frame):
option1_map = {
"Person": 1,
"Background": 2,
"Whole Frame": 3
}
option2_map = {
"Blur": 1,
"Sepia": 2,
"Pixelate": 3,
"Emboss": 4,
"Edge Enhance": 5,
"Increase Brightness": 'i',
"Decrease Brightness": 'd'
}
option1 = option1_map.get(option1, 1)
option2 = option2_map.get(option2, 1)
if option1 == 1: # Apply effects to the person
person = segmen.removeBG(frame, (0, 0, 0), cutThreshold=0.8)
background = cv2.subtract(frame, person)
if option2 == 1:
person = cv2.GaussianBlur(person, (15, 15), 0)
elif option2 == 2:
person = apply_sepia_filter(person)
elif option2 == 3:
person = pixelate(person)
elif option2 == 4:
person = apply_emboss_filter(person)
elif option2 == 5:
person = apply_edge_enhance(person)
elif option2 == 'i':
# person = brightness_control(person, 30)
background = brightness_control(background, -30)
elif option2 == 'd':
person = brightness_control(person, -30)
frame = cv2.add(person, background)
elif option1 == 2:
person = segmen.removeBG(frame, (0, 0, 0), cutThreshold=0.8)
background = cv2.subtract(frame, person)
if option2 == 1:
background = cv2.GaussianBlur(background, (15, 15), 0)
elif option2 == 2:
background = apply_sepia_filter(background)
elif option2 == 3:
background = pixelate(background)
elif option2 == 4:
background = apply_emboss_filter(background)
elif option2 == 5:
background = apply_edge_enhance(background)
elif option2 == 'i':
person = brightness_control(person, -30)
# background = brightness_control(background, 30)
elif option2 == 'd':
background = brightness_control(background, -30)
frame = cv2.add(person, background)
elif option1 == 3:
if option2 == 1:
frame = cv2.GaussianBlur(frame, (15, 15), 0)
elif option2 == 2:
frame = apply_sepia_filter(frame)
elif option2 == 3:
frame = pixelate(frame)
elif option2 == 4:
frame = apply_emboss_filter(frame)
elif option2 == 5:
frame = apply_edge_enhance(frame)
elif option2 == 'i':
frame = brightness_control(frame, 50)
elif option2 == 'd':
frame = brightness_control(frame, -50)
return frame
def process_image(img, option1, option2):
frame = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
output_frame = final(option1, option2, frame)
return cv2.cvtColor(output_frame, cv2.COLOR_BGR2RGB)
# def process_image(img, option1, option2, button):
# frame = cv2.cvtColor(img, cv2.COLOR_RGB2BGR)
# output_frame = final(option1, option2, frame)
# return cv2.cvtColor(output_frame, cv2.COLOR_BGR2RGB)
with gr.Blocks() as demo:
with gr.Row():
img=gr.Image(source="webcam")
io=gr.Image()
r1=gr.Radio(["Person", "Background", "Whole Frame"])
r2=gr.Radio(["Blur", "Sepia", "Pixelate", "Emboss", "Edge Enhance", "Increase Brightness", "Decrease Brightness"])
btn = gr.Button(value="Submit")
btn.click(process_image, inputs=[img,r1,r2], outputs=[io])
# iface = gr.Interface(
# fn=process_image,
# inputs=[
# gr.Image(source="webcam"),
# gr.Radio(["Person", "Background", "Whole Frame"]),
# gr.Radio(["Blur", "Sepia", "Pixelate", "Emboss", "Edge Enhance", "Increase Brightness", "Decrease Brightness"]),
# gr.Button(label="Apply Effect")
# ],
# outputs=gr.Image(),
# live=True
# )
# iface.launch()
demo.launch()
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