app.py

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
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)


def do_interpolation(frame1, frame2, interpolation):
    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"{frame1}_to_{frame2}_out.mp4", frames, fps=25)
    return f"{frame1}_to_{frame2}_out.mp4"
    
def get_frames(video_in, step, name, resize_w):
    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"{name}_{step}{str(i)}.jpg",frame)
        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)
    
    return type + "_result.mp4"

    
def infer(url_in,interpolation,fps_output,resize_n,winsize):
    
    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 = break_vid[0]
    fps = break_vid[1]
    print(f"ORIGIN FPS: {fps}")
    n_frame = int(15*fps) #limited to 15 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}_", 0)
            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"{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")

    files = final_vid

    depth_map = cv2.VideoCapture(final_vid)
    print("total frames: " + str(len(result_frames)))

    ret, fr1 = depth_map.read()
    prvs = cv2.cvtColor(fr1, cv2.COLOR_RGBA2GRAY)
    hsv = np.zeros_like(fr1)
    hsv[..., 1] = 255
    res = np.zeros_like(prvs)
    flow = res
    while(depth_map.isOpened()):
      ret, fr2 = depth_map.read()
      if ret == False:
        break
      nxt = cv2.cvtColor(fr2, cv2.COLOR_RGBA2GRAY)
      fl = cv2.calcOpticalFlowFarneback(prvs, nxt, flow, 0.5, 3, winsize, 3, 5, 1.2, 0)
      mag, ang = cv2.cartToPolar(fl[..., 0], fl[..., 1])
      hsv[..., 0] = ang*180/np.pi/2
      hsv[..., 2] = cv2.normalize(mag, None, 0, 255, cv2.NORM_MINMAX)
      rgb = cv2.cvtColor(hsv, cv2.COLOR_HSV2RGB)
      rgb = cv2.cvtColor(rgb, cv2.COLOR_RGBA2GRAY)
      alpha = 1.0/len(result_frames)
      beta = (1.0 - alpha)
      res = cv2.addWeighted(rgb, alpha, res, beta, 0.0, res)
      prvs = nxt

    cv2.imwrite('opticalfb.png', res)
    depth_map.release()
    cv2.destroyAllWindows()

    return final_vid, files, 'opticalfb.png'


def logscale(linear):
    return int(math.pow(2, linear))


title="""
<div style="text-align: center; max-width: 500px; margin: 0 auto;">
        <div
        style="
            display: inline-flex;
            align-items: center;
            gap: 0.8rem;
            font-size: 1.75rem;
            margin-bottom: 10px;
        "
        >
        <h1 style="font-weight: 600; margin-bottom: 7px;">
            Video interpolation with FILM
        </h1>
        
        </div>
       <p> This space uses FILM to generate interpolation frames in a video you need to 'tween'.<br />
       Generation is limited to 15 seconds, from the beginning of your video input.<br />
       <a style="display:inline-block" href="https://huggingface.co/spaces/freealise/video_frame_interpolation?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a> 
       </p>
    </div>
"""

with gr.Blocks() as demo:
    with gr.Column():
        gr.HTML(title)
        with gr.Row():
            with gr.Column():
                url_input = gr.Textbox(value="./examples/streetview.mp4", label="URL")
                resize_num = gr.Slider(minimum=1, maximum=4096, step=1, value=256, label="Resize to width: ")
                winsize_num = gr.Slider(minimum=1, maximum=256, step=1, value=15, label="Motion detection window size: ")
                with gr.Row():
                    interpolation_slider = gr.Slider(minimum=1, maximum=5, step=1, value=1, label="Interpolation Steps: ")
                    interpolation = gr.Label(value=2, show_label=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.Label(value=1, show_label=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()
                depth_output = gr.ImageEditor(image_mode="L", interactive=True, label="Depth map")
    
    gr.Examples(
        examples=[["./examples/streetview.mp4", 1, 0, 256, 15]],
        fn=infer,
        inputs=[url_input,interpolation_slider,fps_output_slider,resize_num,winsize_num],
        outputs=[video_output,file_output,depth_output],
        cache_examples=True
    )
    
    submit_btn.click(fn=infer, inputs=[url_input,interpolation_slider,fps_output_slider,resize_num,winsize_num], outputs=[video_output, file_output, depth_output])

demo.launch()