import os os.system("git clone https://github.com/google-research/frame-interpolation") import sys sys.path.append("frame-interpolation") import math import cv2 import numpy as np import tensorflow as tf import mediapy from PIL import Image 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") from eval import interpolator, util interpolator = interpolator.Interpolator(model, None) ffmpeg_path = util.get_ffmpeg_path() mediapy.set_ffmpeg(ffmpeg_path) def do_interpolation(frame1, frame2, interpolation, n): print("tween frames: " + str(interpolation)) print(frame1, frame2) input_frames = [frame1, frame2] frames = list( util.interpolate_recursively_from_files( input_frames, int(interpolation), interpolator)) #print(frames) mediapy.write_video(f"{n}_to_{n+1}_out.mp4", frames, fps=25) return f"{n}_to_{n+1}_out.mp4" def get_frames(video_in, step, name, n): frames = [] cap = cv2.VideoCapture(video_in) cframes = int(cap.get(cv2.CAP_PROP_FRAME_COUNT)) cfps = int(cap.get(cv2.CAP_PROP_FPS)) print(f'frames: {cframes}, fps: {cfps}') #resize the video #clip = VideoFileClip(video_in) #check fps #if cfps > 25: # print("video rate is over 25, resetting to 25") # clip_resized = clip.resize(height=1024) # clip_resized.write_videofile("video_resized.mp4", fps=25) #else: # print("video rate is OK") # clip_resized = clip.resize(height=1024) # clip_resized.write_videofile("video_resized.mp4", fps=cfps) #print("video resized to 1024 height") # Opens the Video file with CV2 #cap = cv2.VideoCapture("video_resized.mp4") fps = cap.get(cv2.CAP_PROP_FPS) print("video fps: " + str(fps)) i=0 while(cap.isOpened()): ret, frame = cap.read() if ret == False: break #if resize_w > 0: #resize_h = resize_w / 2.0 #frame = cv2.resize(frame, (int(resize_w), int(resize_h))) cv2.imwrite(f"{str(n)}_{name}_{step}{str(i)}.png", frame) frames.append(f"{str(n)}_{name}_{step}{str(i)}.png") i+=1 cap.release() cv2.destroyAllWindows() print("broke the video into frames") return frames, fps def create_video(frames, fps, type): print("building video result") imgs = [] for j, img in enumerate(frames): imgs.append(cv2.cvtColor(cv2.imread(img).astype(np.uint8), cv2.COLOR_BGR2RGB)) mediapy.write_video(type + "_result.mp4", imgs, fps=fps) return type + "_result.mp4" def infer(f_in, interpolation, fps_output): fps_output = logscale(fps_output) # 1. break video into frames and get FPS #break_vid = get_frames(url_in, "vid_input_frame", "origin", resize_n) frames_list = f_in #break_vid[0] fps = 1 #break_vid[1] print(f"ORIGIN FPS: {fps}") n_frame = int(300) #limited to 300 frames #n_frame = len(frames_list) if n_frame >= len(frames_list): print("video is shorter than the cut value") n_frame = len(frames_list) # 2. prepare frames result arrays result_frames = [] print("set stop frames to: " + str(n_frame)) for idx, frame in enumerate(frames_list[0:int(n_frame)]): if idx < len(frames_list) - 1: next_frame = frames_list[idx+1] interpolated_frames = do_interpolation(frame, next_frame, interpolation, idx) # should return a list of interpolated frames break_interpolated_video = get_frames(interpolated_frames, "interpol", f"{idx}_", -1) print(break_interpolated_video[0]) for j, img in enumerate(break_interpolated_video[0][0:len(break_interpolated_video[0])-1]): print(f"IMG:{img}") os.rename(img, f"{idx}_to_{idx+1}_{j}.png") result_frames.append(f"{idx}_to_{idx+1}_{j}.png") print("frames " + str(idx) + " & " + str(idx+1) + "/" + str(n_frame) + ": done;") #print(f"CURRENT FRAMES: {result_frames}") result_frames.append(f"{frames_list[n_frame-1]}") final_vid = create_video(result_frames, fps_output, "interpolated") files = final_vid print("interpolated frames: " + str(len(frames_list)) + " -> " + str(len(result_frames))) cv2.destroyAllWindows() return final_vid, files def logscale(linear): return int(math.pow(2, linear)) def linscale(linear): return int(math.log2(linear)) def sharpest(fl, i): break_vid = get_frames(fl, "vid_input_frame", "origin", i) blur_s = [] for jdx, fr in enumerate(break_vid[0]): blur_s.append(cv2.Laplacian(cv2.cvtColor(cv2.imread(fr).astype(np.uint8), cv2.COLOR_BGR2GRAY), cv2.CV_64F).var()) print(str(int(blur_s[jdx]))) mx = np.argmax(blur_s) fl = break_vid[0][mx] print(str(i) +'th file, sharpest frame: '+str(mx)+', name: '+fl) return fl def sortFiles(e): e = e.split('/') return e[len(e)-1] def loadf(f): if f != None and f[0] != None: f.sort(key=sortFiles) fnew = [] for i, fl in enumerate(f): ftype = fl.split('/') if ftype[len(ftype)-1].split('.')[1] == 'mp4': fnew.append(sharpest(fl, i)) else: fnew.append(fl) return fnew, fnew else: return f, f title="""

Video interpolation from images with FILM

This space uses FILM to generate interpolation frames in a set of image files you need to turn into a video. Limited to 300 uploaded frames, from the beginning of your input.
Duplicate Space

""" with gr.Blocks() as demo: with gr.Column(): gr.HTML(title) with gr.Row(): with gr.Column(): with gr.Accordion(label="Upload files here", open=True): files_input = gr.File(file_count="multiple", file_types=['image', '.mp4']) gallery_input = gr.Gallery(label="Slideshow", preview=True, columns=8192, interactive=False) files_input.change(fn=loadf, inputs=[files_input], outputs=[files_input, gallery_input]) with gr.Row(): interpolation_slider = gr.Slider(minimum=1, maximum=5, step=1, value=1, label="Interpolation Steps: ") interpolation = gr.Number(value=1, show_label=False, interactive=False) interpolation_slider.change(fn=logscale, inputs=[interpolation_slider], outputs=[interpolation]) with gr.Row(): fps_output_slider = gr.Slider(minimum=0, maximum=5, step=1, value=0, label="FPS output: ") fps_output = gr.Number(value=1, show_label=False, interactive=False) fps_output_slider.change(fn=logscale, inputs=[fps_output_slider], outputs=[fps_output]) submit_btn = gr.Button("Submit") with gr.Column(): video_output = gr.Video() file_output = gr.File() gr.Examples( examples=[[["./examples/0.png", "./examples/1.png", "./examples/2.png", "./examples/3.png", "./examples/4.png"], 1, 0]], fn=infer, inputs=[files_input, interpolation_slider, fps_output_slider], outputs=[video_output, file_output], cache_examples=True ) submit_btn.click(fn=infer, inputs=[files_input, interpolation_slider, fps_output_slider], outputs=[video_output, file_output]) demo.launch()