import os os.system("git clone https://github.com/google-research/frame-interpolation") import sys sys.path.append("frame-interpolation") import numpy as np import tensorflow as tf import mediapy from PIL import Image from eval import interpolator, util import gradio as gr from huggingface_hub import snapshot_download from image_tools.sizes import resize_and_crop model = snapshot_download(repo_id="akhaliq/frame-interpolation-film-style") interpolator = interpolator.Interpolator(model, None) 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): 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, interpolator)) mediapy.write_video("out.mp4", frames, fps=30) return "out.mp4" title="frame-interpolation" description="Gradio demo for FILM: Frame Interpolation for Large Scene Motion. To use it, simply upload your images and add the times to interpolate number or click on one of the examples to load them. Read more at the links below." article = "

FILM: Frame Interpolation for Large Motion | Github Repo

" examples=[['cat3.jpeg','cat4.jpeg',2]] gr.Interface(predict,[gr.inputs.Image(type='filepath'),gr.inputs.Image(type='filepath'),gr.inputs.Slider(minimum=2,maximum=4,step=1)],"playable_video",title=title,description=description,article=article,examples=examples).launch(enable_queue=True)