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import gradio as gr
import os
import cv2
import numpy as np
from PIL import Image
from moviepy.editor import *
from gradio_client import Client
mmpose_client = Client("https://fffiloni-mmpose-estimation.hf.space/--replicas/67vw9/")
#mmpose = gr.Interface.load(name="spaces/fffiloni/mmpose-estimation")
def get_frames(video_in):
frames = []
#resize the video
clip = VideoFileClip(video_in)
#check fps
if clip.fps > 30:
print("vide rate is over 30, resetting to 30")
clip_resized = clip.resize(height=512)
clip_resized.write_videofile("video_resized.mp4", fps=30)
else:
print("video rate is OK")
clip_resized = clip.resize(height=512)
clip_resized.write_videofile("video_resized.mp4", fps=clip.fps)
print("video resized to 512 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
cv2.imwrite('kang'+str(i)+'.jpg',frame)
frames.append('kang'+str(i)+'.jpg')
i+=1
cap.release()
cv2.destroyAllWindows()
print("broke the video into frames")
return frames, fps
def get_mmpose_filter(i):
#image = Image.open(i)
#image = np.array(image)
mmpose_result = mmpose_client.predict(
i, # filepath in 'img' Image component
api_name="/predict"
)
print(mmpose_result)
image = mmpose_result[1]
image = Image.open(image)
#image = Image.fromarray(image)
image.save("mmpose_frame_" + str(i) + ".jpeg")
return "mmpose_frame_" + str(i) + ".jpeg"
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 convertG2V(imported_gif):
clip = VideoFileClip(imported_gif.name)
clip.write_videofile("my_gif_video.mp4")
return "my_gif_video.mp4"
def infer(video_in):
# 1. break video into frames and get FPS
break_vid = get_frames(video_in)
frames_list= break_vid[0]
fps = break_vid[1]
#n_frame = int(trim_value*fps)
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 i in frames_list[0:int(n_frame)]:
mmpose_frame = get_mmpose_filter(i)
result_frames.append(mmpose_frame)
print("frame " + i + "/" + str(n_frame) + ": done;")
final_vid = create_video(result_frames, fps, "mmpose")
files = [final_vid]
return final_vid, files
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 to MMPose
</h1>
</div>
<p>Convert any video or gif to a MMPose sequence. <br />
Once you got your converted video, you can use it with the <a href="https://huggingface.co/spaces/YueMafighting/FollowYourPose" target="_blank">FollowYourPose</a> demo</p>
</div>
"""
with gr.Blocks() as demo:
with gr.Column():
gr.HTML(title)
with gr.Row():
with gr.Column():
video_input = gr.Video()
gif_input = gr.File(label="import a GIF instead", file_types=['.gif'])
gif_input.change(fn=convertG2V, inputs=gif_input, outputs=video_input)
submit_btn = gr.Button("Submit")
with gr.Column():
video_output = gr.Video()
file_output = gr.Files()
gr.Examples(
examples=["./examples/childishgambino.mp4", "./examples/jimmyfallon.mp4"],
fn=infer,
inputs=[video_input],
outputs=[video_output,file_output],
cache_examples=False
)
submit_btn.click(fn=infer, inputs=[video_input], outputs=[video_output, file_output])
demo.launch() |