import cv2 from PIL import Image import numpy as np from rembg import remove import os import shutil import glob import moviepy.editor as mp from moviepy.editor import * 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 video_to_images(video_path, images_path): # Open video cam = cv2.VideoCapture(video_path) # Get FPS fps = cam.get(cv2.CAP_PROP_FPS) # Extract audio clip = mp.VideoFileClip(video_path) clip.audio.write_audiofile("./audio.mp3") # Create folder for images if not os.path.exists(images_path): os.makedirs(images_path) else: shutil.rmtree(images_path) os.makedirs(images_path) # Go through frames of video frameno = 0 while(True): ret,frame = cam.read() if ret: # if video is still left continue creating images name = images_path + str(frameno).zfill(5) + '.png' print ('new frame captured... ', frameno) # Save frame cv2.imwrite(name, frame, [int(cv2.IMWRITE_PNG_COMPRESSION), 0]) frameno += 1 else: break # Close video cam.release() cv2.destroyAllWindows() return fps def images_to_video(images_path, video_export_path, fps): # Get a list of PNG images on the "test_images" folder images = glob.glob(images_path + "*.png") # Sort images by name images = sorted(images) # Read the first image to get the frame size frame = cv2.imread(images[0]) height, width, layers = frame.shape temp_video_path = './temp-video.mp4' # Codec #fourcc = cv2.VideoWriter_fourcc(*"mp4v") fourcc = cv2.VideoWriter_fourcc(*'XVID') #fourcc = cv2.VideoWriter_fourcc(*'MPEG') # Create final video video = cv2.VideoWriter(filename=temp_video_path, fourcc=fourcc, fps=fps, frameSize=(width,height)) # Read each image and write it to the video for i, image in enumerate(images): print("Writing frame to video ", i, '/' , len(images)) # Read the image using OpenCV frame = cv2.imread(image) # Write frame to video video.write(frame) # Exit the video writer video.release() # Open final video videoclip = VideoFileClip(temp_video_path) # Add audio to final video audioclip = AudioFileClip("./audio.mp3") new_audioclip = CompositeAudioClip([audioclip]) videoclip.audio = new_audioclip # Save final video videoclip.write_videofile(video_export_path, audio_codec='aac', codec='libx264') # Delete temp files os.remove(temp_video_path) os.remove("./audio.mp3") 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 = background_blur.copy() subject_on_blur_background.paste(background, (0,0), subject) # Blend the subject and the blur background result = Image.blend(background_blur, subject_on_blur_background, amount_subject) return result def video_motion_blur(video_path, export_video_path, distance_blur, amount_blur, amount_subject): # Image folder images_path = './images/' # Convert video to images and save FPS fps = video_to_images(video_path, images_path) # Create list of images image_path_list = glob.glob(images_path + "*.png") # Sort images by name image_path_list = sorted(image_path_list) # Create folder for blur images blur_images_path = './blur_images/' if not os.path.exists(blur_images_path): os.makedirs(blur_images_path) else: shutil.rmtree(blur_images_path) os.makedirs(blur_images_path) # Go through image folder count = 0 for filename in image_path_list: # Open image an PIL image img =Image.open(filename) # Motion blur image blur_img = background_motion_blur(img, distance_blur, amount_blur, amount_subject) # Save blurred image blur_img.save(blur_images_path + str(count).zfill(5) + '.png') print('motion blur', str(count), '/', len(image_path_list) ) count += 1 # Convert blurred images to final video images_to_video(blur_images_path, export_video_path, fps) # Delete temp folders shutil.rmtree(images_path) shutil.rmtree(blur_images_path)