import os os.system("git clone https://github.com/google-research/frame-interpolation") import sys sys.path.append("frame-interpolation") import cv2 import numpy as np import tensorflow as tf import mediapy from PIL import Image import base64 import gradio as gr import tempfile from huggingface_hub import snapshot_download from image_tools.sizes import resize_and_crop from moviepy.editor import * 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) SECRET_TOKEN = os.getenv('SECRET_TOKEN', 'default_secret') def base64_to_video(base64_string, output_file): video_data = base64.b64decode(base64_string) with open(output_file, 'wb') as f: f.write(video_data) def do_interpolation(frame1, frame2, times_to_interpolate): print(frame1, frame2) input_frames = [frame1, frame2] #times_to_interpolate = 2 frames = list( util.interpolate_recursively_from_files( input_frames, times_to_interpolate, interpolator)) #print(frames) mediapy.write_video(f"{frame1}_to_{frame2}_out.mp4", frames, fps=12) return f"{frame1}_to_{frame2}_out.mp4" def get_frames(video_in, step, name): frames = [] #resize the video clip = VideoFileClip(video_in) #check fps if clip.fps > 30: print("vide rate is over 30, resetting to 30") # note: we used to resize the input video, but this is gonna prevent us from working with portrait videos, so.. # clip_resized = clip.resize(height=576) clip_resized = clip clip_resized.write_videofile("video_resized.mp4", fps=30, bitrate="12000k") else: print("video rate is OK") # note: we used to resize the input video, but this is gonnal prevent us from working with portrait videos, so.. # clip_resized = clip.resize(height=576) clip_resized = clip clip_resized.write_videofile("video_resized.mp4", fps=clip.fps, bitrate="12000k") print("video resized to 576 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 # we could use png to avoid any compression artifact, but it takes much more space! # alternatively, let's just bump the quality from 95 to 98 for now cv2.imwrite(f"{name}_{step}{str(i)}.jpg", frame, [int(cv2.IMWRITE_JPEG_QUALITY), 98]) frames.append(f"{name}_{step}{str(i)}.jpg") 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") clip = ImageSequenceClip(frames, fps=fps) clip.write_videofile(type + "_result.mp4", fps=fps, bitrate="12000k") return type + "_result.mp4" def infer(secret_token, video_in_base64, interpolation, fps_output): if secret_token != SECRET_TOKEN: raise gr.Error(f'Invalid secret token. Please fork the original space if you want to use it for yourself.') # Decode the base64 string to a video file video_in = "video_in.mp4" # or choose any other filename/path base64_to_video(video_in_base64, video_in) # 1. break video into frames and get FPS break_vid = get_frames(video_in, "vid_input_frame", "origin") frames_list= break_vid[0] fps = break_vid[1] print(f"ORIGIN FPS: {fps}") n_frame = int(4*fps) #limited to 4 seconds #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) # should return a list of 3 interpolated frames break_interpolated_video = get_frames(interpolated_frames, "interpol",f"{idx}_") 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}") # we could use png to avoid any compression artifact, but it takes much more space # alternatively, let's just bump the quality from 95 to 98 for now os.rename(img, f"{frame}_to_{next_frame}_{j}.jpg") result_frames.append(f"{frame}_to_{next_frame}_{j}.jpg") 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") encoded_string = "" # Convert video to base64 with open(final_vid, "rb") as video_file: encoded_string = base64.b64encode(video_file.read()).decode('utf-8') return f"data:video/mp4;base64,{encoded_string}" title="""test space""" with gr.Blocks() as demo: gr.HTML("""

This UI-less space is a REST API to programmatically interpolate MP4s.

""") secret_token = gr.Textbox(label="Secret token") video_input = gr.Textbox(label="Video Base64") interpolation = gr.Slider(minimum=1, maximum=8, step=1, value=4, label="Interpolation Steps") fps_output = gr.Slider(minimum=1, maximum=120, step=1, value=24, label="FPS output") submit_btn = gr.Button("Submit") video_output = gr.Textbox() submit_btn.click(fn=infer, inputs=[secret_token, video_input, interpolation, fps_output], outputs=video_output) demo.launch()