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import os | |
import sys | |
import cv2 | |
import mediapy | |
import numpy as np | |
from eval import interpolator, util | |
from huggingface_hub import snapshot_download | |
from image_tools.sizes import resize_and_crop | |
from moviepy.editor import CompositeVideoClip | |
from moviepy.editor import VideoFileClip as vfc | |
from PIL import Image | |
# My installs | |
os.system("git clone https://github.com/google-research/frame-interpolation") | |
sys.path.append("frame-interpolation") | |
# get key positions at which frame needs to be generated | |
def list_of_positions(num_contours, num_frames=100): | |
positions = [] | |
for i in range(0, num_frames): | |
positions.append(int(num_contours / num_frames * i)) | |
return positions | |
def contourfinder(image1, image2, text=None, num_frames=100): | |
# Create two blank pages to write into | |
# I just hardcoded 1024*1024 as the size, ideally this should be np.shape(image1) | |
blank = np.zeros((2048, 2048, 3), dtype="uint8") | |
blank2 = np.zeros((2048, 2048, 3), dtype="uint8") | |
# Threshold and contours for image 1 and 2 | |
threshold = cv2.Canny(image=image1, threshold1=100, threshold2=200) | |
contours, hierarchies = cv2.findContours( | |
threshold, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE | |
) | |
threshold2 = cv2.Canny(image=image2, threshold1=100, threshold2=200) | |
contours2, hierarchies2 = cv2.findContours( | |
threshold2, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE | |
) | |
# Initialize three empty videos | |
vid1 = cv2.VideoWriter( | |
"vid1.mp4", cv2.VideoWriter_fourcc(*"mp4v"), 24, threshold.shape | |
) | |
vid2 = cv2.VideoWriter( | |
"vid2.mp4", cv2.VideoWriter_fourcc(*"mp4v"), 24, threshold.shape | |
) | |
text_vid = cv2.VideoWriter( | |
"text_vid.mp4", cv2.VideoWriter_fourcc(*"mp4v"), 10, threshold.shape | |
) | |
# Get positions | |
positions = list_of_positions((len(contours))) | |
frames = [] | |
# Loop over contours adding them to blank image then writing to video | |
for i in range(0, len(contours)): | |
cv2.drawContours( | |
blank, contours=contours, contourIdx=i, color=(125, 200, 255), thickness=1 | |
) | |
if i in positions: | |
frames.append(blank) | |
# Complile to video | |
vid1.write(blank) | |
vid1.release() | |
clip1 = vfc("/home/user/app/vid1.mp4") | |
# print(f"Type clip 1{type(clip1)}") | |
positions = list_of_positions((len(contours2))) | |
for i in range(0, len(contours2)): | |
cv2.drawContours( | |
blank2, contours=contours2, contourIdx=i, color=(125, 200, 255), thickness=1 | |
) | |
if i in positions: | |
frames.append(blank2) | |
vid2.write(blank2) | |
vid2.release() | |
clip3 = vfc("/home/user/app/vid2.mp4") | |
# Next is the text vid | |
if text != None: | |
# Reading an image in default mode | |
image = np.zeros(original.shape, dtype="uint8") | |
# font | |
font = cv2.FONT_HERSHEY_COMPLEX | |
# org | |
org = (10, 400) | |
# fontScale | |
fontScale = 3 | |
# Blue color in BGR | |
color = (186, 184, 108) | |
# Line thickness of 2 px | |
thickness = 4 | |
def text_frames(text, image, org): | |
spacing = 55 # spacing between letters | |
blink = image | |
cv2.imwrite(f"blink.png", blink) | |
for i in range(0, len(text) - 1): | |
text_vid.write(blink) | |
# Using cv2.putText() method | |
image = cv2.putText( | |
image, text[i], org, font, fontScale, color, thickness, cv2.LINE_AA | |
) | |
# Take care of org spacing | |
org = (org[0] + spacing, org[1]) | |
if text[i].isupper(): | |
org = (org[0] + spacing + 1, org[1]) | |
print(f"Upper {text[i]}") | |
print(org) | |
# Displaying the image | |
cv2.imwrite(f"text_im{i}.png", image) | |
# Complile to video | |
text_vid.write(image) | |
text_vid.release() | |
text_frames(text, image, org) | |
return clip1, clip3 | |
def load_model(model_name): | |
model = interpolator.Interpolator(snapshot_download(repo_id=model_name), None) | |
return model | |
model_names = [ | |
"akhaliq/frame-interpolation-film-style", | |
"NimaBoscarino/frame-interpolation_film_l1", | |
"NimaBoscarino/frame_interpolation_film_vgg", | |
] | |
models = {model_name: load_model(model_name) for model_name in model_names} | |
ffmpeg_path = util.get_ffmpeg_path() | |
mediapy.set_ffmpeg(ffmpeg_path) | |
def resize(width, img): | |
basewidth = width | |
img = Image.open(img) | |
wpercent = basewidth / float(img.size[0]) | |
hsize = int((float(img.size[1]) * float(wpercent))) | |
img = img.resize((basewidth, hsize), Image.ANTIALIAS) | |
return img | |
def resize_img(img1, img2): | |
img_target_size = Image.open(img1) | |
img_to_resize = resize_and_crop( | |
img2, | |
( | |
img_target_size.size[0], | |
img_target_size.size[1], | |
), # set width and height to match img1 | |
crop_origin="middle", | |
) | |
img_to_resize.save("resized_img2.png") | |
def predict(frame1, frame2, times_to_interpolate, model_name): | |
model = models[model_name] | |
img1 = cv2.imread(frame1) | |
img2 = cv2.imread(frame2) | |
frame1 = resize(256, frame1) | |
frame2 = resize(256, frame2) | |
frame1.save("test1.png") | |
frame2.save("test2.png") | |
resize_img("test1.png", "test2.png") | |
input_frames = ["test1.png", "resized_img2.png"] | |
frames = list( | |
util.interpolate_recursively_from_files( | |
input_frames, times_to_interpolate, model | |
) | |
) | |
mediapy.write_video("out.mp4", frames, fps=5) | |
print(f"TYPES....{type(img1)},{type(img2)} SHAPES{img1.shape} Img {img1}") | |
clip1, clip3 = contourfinder(img1, img2) # has a third text option | |
# Use open CV and moviepy code | |
# So we move from open CV video 1 to out.mp4 to open CV video2 | |
clip1 = clip1 | |
clip2 = vfc("out.mp4").resize(8).set_start(clip1.duration - 0.5).crossfadein(2) | |
clip3 = clip3.set_start((clip1.duration - 0.5) + (clip2.duration)).crossfadein(2) | |
new_clip = CompositeVideoClip([clip1, clip2, clip3]) | |
new_clip.write_videofile("out.mp4") | |
return "out.mp4" | |