Spaces:
Runtime error
Runtime error
File size: 3,543 Bytes
0b756df |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 |
import os
import cv2
import time
import glob
import shutil
import platform
import datetime
import subprocess
from threading import Thread
from moviepy.editor import VideoFileClip, ImageSequenceClip
from moviepy.video.io.ffmpeg_tools import ffmpeg_extract_subclip
def trim_video(video_path, output_path, start_frame, stop_frame):
video_name, _ = os.path.splitext(os.path.basename(video_path))
trimmed_video_filename = video_name + "_trimmed" + ".mp4"
temp_path = os.path.join(output_path, "trim")
os.makedirs(temp_path, exist_ok=True)
trimmed_video_file_path = os.path.join(temp_path, trimmed_video_filename)
video = VideoFileClip(video_path)
fps = video.fps
start_time = start_frame / fps
duration = (stop_frame - start_frame) / fps
trimmed_video = video.subclip(start_time, start_time + duration)
trimmed_video.write_videofile(
trimmed_video_file_path, codec="libx264", audio_codec="aac"
)
trimmed_video.close()
video.close()
return trimmed_video_file_path
def open_directory(path=None):
if path is None:
return
try:
os.startfile(path)
except:
subprocess.Popen(["xdg-open", path])
class StreamerThread(object):
def __init__(self, src=0):
self.capture = cv2.VideoCapture(src)
self.capture.set(cv2.CAP_PROP_BUFFERSIZE, 2)
self.FPS = 1 / 30
self.FPS_MS = int(self.FPS * 1000)
self.thread = None
self.stopped = False
self.frame = None
def start(self):
self.thread = Thread(target=self.update, args=())
self.thread.daemon = True
self.thread.start()
def stop(self):
self.stopped = True
self.thread.join()
print("stopped")
def update(self):
while not self.stopped:
if self.capture.isOpened():
(self.status, self.frame) = self.capture.read()
time.sleep(self.FPS)
class ProcessBar:
def __init__(self, bar_length, total, before="⬛", after="🟨"):
self.bar_length = bar_length
self.total = total
self.before = before
self.after = after
self.bar = [self.before] * bar_length
self.start_time = time.time()
def get(self, index):
total = self.total
elapsed_time = time.time() - self.start_time
average_time_per_iteration = elapsed_time / (index + 1)
remaining_iterations = total - (index + 1)
estimated_remaining_time = remaining_iterations * average_time_per_iteration
self.bar[int(index / total * self.bar_length)] = self.after
info_text = f"({index+1}/{total}) {''.join(self.bar)} "
info_text += f"(ETR: {int(estimated_remaining_time // 60)} min {int(estimated_remaining_time % 60)} sec)"
return info_text
logo_image = cv2.imread("./assets/images/logo.png", cv2.IMREAD_UNCHANGED)
def add_logo_to_image(img, logo=logo_image):
logo_size = int(img.shape[1] * 0.1)
logo = cv2.resize(logo, (logo_size, logo_size))
if logo.shape[2] == 4:
alpha = logo[:, :, 3]
else:
alpha = np.ones_like(logo[:, :, 0]) * 255
padding = int(logo_size * 0.1)
roi = img.shape[0] - logo_size - padding, img.shape[1] - logo_size - padding
for c in range(0, 3):
img[roi[0] : roi[0] + logo_size, roi[1] : roi[1] + logo_size, c] = (
alpha / 255.0
) * logo[:, :, c] + (1 - alpha / 255.0) * img[
roi[0] : roi[0] + logo_size, roi[1] : roi[1] + logo_size, c
]
return img
|