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import cv2 | |
from PIL import Image | |
import numpy as np | |
from rembg import remove | |
def cv_to_pil(img): | |
return Image.fromarray(cv2.cvtColor(img, cv2.COLOR_BGRA2RGBA)) | |
def pil_to_cv(img): | |
return cv2.cvtColor(np.array(img), cv2.COLOR_RGBA2BGRA) | |
def motion_blur(img, distance, amount): | |
# Convert to RGBA | |
img = img.convert('RGBA') | |
# Convert pil to cv | |
cv_img = pil_to_cv(img) | |
# Generating the kernel | |
kernel_motion_blur = np.zeros((distance, distance)) | |
kernel_motion_blur[int((distance-1)/2), :] = np.ones(distance) | |
kernel_motion_blur = kernel_motion_blur / distance | |
# Applying the kernel to the input image | |
output = cv2.filter2D(cv_img, -1, kernel_motion_blur) | |
# Convert cv to pil | |
blur_img = cv_to_pil(output).convert('RGBA') | |
# Blend the original image and the blur image | |
final_img = Image.blend(img, blur_img, amount) | |
return final_img | |
def background_motion_blur(background, distance_blur, amount_blur, amount_subject): | |
# Remove background | |
subject = remove(background) | |
# Blur the background | |
background_blur = motion_blur(background, distance_blur, amount_blur) | |
# Put the subject on top of the blur background | |
subject_on_blur_background = Image.alpha_composite(background_blur, subject) | |
# Blend the subject and the blur background | |
result = Image.blend(background_blur, subject_on_blur_background, amount_subject) | |
return result |