testing aria2c

app.py

@@ -16,6 +16,7 @@ import gradio as gr
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model, preprocess = clip.load("ViT-B/32")
 
+
 def select_video_format(url, format_note='480p', ext='mp4'):
     defaults = ['480p', '360p','240p','144p']
     ydl_opts = {}
@@ -32,10 +33,14 @@ def select_video_format(url, format_note='480p', ext='mp4'):
     print(f'format selected: {format}')
     return(format, format_id, fps)
 
-# to-do: delete saved videos      
+
+# to-do: delete saved videos    
+# testing aria2c  
 def download_video(url,format_id, n_keep=10):
     ydl_opts = {
       'format':format_id,
+      'external_downloader' : 'aria2c',
+      'external_downloader_args' :['--max-connection-per-server=16','--dir=videos'],
       'outtmpl': "videos/%(id)s.%(ext)s"}
     # create a directory for saved videos
     video_path = Path('videos')
@@ -122,7 +127,7 @@ def captioned_strip(images, caption=None, times=None, rows=1):
           (255, 255, 255), font=font_small)
     return img
 
-def run_inference(url, sampling_interval, search_query, bs=256):
+def run_inference(url, sampling_interval, search_query, bs=526):
     skip_frames, path_frames= vid2frames(url,sampling_interval)
     filenames = sorted(path_frames.glob('*.jpg'),key=lambda p: int(p.stem))
     n_frames = len(filenames)

packages.txt

@@ -1,2 +1,3 @@
 ffmpeg
-fonts-liberation2
+fonts-liberation2
+aria2c