change requirements

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
 pexels-darina-belonogova-7539228.mp4 filter=lfs diff=lfs merge=lfs -text
+*.mp4 filter=lfs diff=lfs merge=lfs -text

app.py

@@ -1,43 +1,41 @@
-import os
-os.system('pip install gradio --upgrade')
-os.system('pip install torch')
-os.system('pip freeze')
 import torch
 import gradio as gr
-model = torch.hub.load("PeterL1n/RobustVideoMatting", "mobilenetv3") # or "resnet50"
+
+model = torch.hub.load("PeterL1n/RobustVideoMatting", "mobilenetv3").cuda()  # or "resnet50"
 
 convert_video = torch.hub.load("PeterL1n/RobustVideoMatting", "converter")
 
+
 def inference(video):
-  convert_video(
-      model,                           # The loaded model, can be on any device (cpu or cuda).
-      input_source=video,        # A video file or an image sequence directory.
-      input_resize=(400, 400),       # [Optional] Resize the input (also the output).
-      downsample_ratio=0.25,           # [Optional] If None, make downsampled max size be 512px.
-      output_type='video',             # Choose "video" or "png_sequence"
-      output_composition='com.mp4',    # File path if video; directory path if png sequence.
-      output_alpha= None,          # [Optional] Output the raw alpha prediction.
-      output_foreground= None,     # [Optional] Output the raw foreground prediction.
-      output_video_mbps=4,             # Output video mbps. Not needed for png sequence.
-      seq_chunk=7,                    # Process n frames at once for better parallelism.
-      num_workers=1,                   # Only for image sequence input. Reader threads.
-      progress=True                    # Print conversion progress.
-  )
-  return 'com.mp4'
-  
+    convert_video(
+        model,                           # The loaded model, can be on any device (cpu or cuda).
+        input_source=video,        # A video file or an image sequence directory.
+        downsample_ratio=0.25,           # [Optional] If None, make downsampled max size be 512px.
+        output_type='video',             # Choose "video" or "png_sequence"
+        output_composition='com.mp4',    # File path if video; directory path if png sequence.
+        output_alpha=None,          # [Optional] Output the raw alpha prediction.
+        output_foreground=None,     # [Optional] Output the raw foreground prediction.
+        output_video_mbps=4,             # Output video mbps. Not needed for png sequence.
+        seq_chunk=12,                    # Process n frames at once for better parallelism.
+        num_workers=1,                   # Only for image sequence input. Reader threads.
+        progress=True                    # Print conversion progress.
+    )
+    return "com.mp4"
+
+
 title = "Robust Video Matting"
 description = "Gradio demo for Robust Video Matting. To use it, simply upload your video, or click one of the examples to load them. Read more at the links below."
 
 article = "<p style='text-align: center'><a href='https://arxiv.org/abs/2108.11515'>Robust High-Resolution Video Matting with Temporal Guidance</a> | <a href='https://github.com/PeterL1n/RobustVideoMatting'>Github Repo</a></p>"
 
-examples = [['pexels-darina-belonogova-7539228.mp4']]
+examples = [["example.mp4"]]
 gr.Interface(
-    inference, 
-    gr.inputs.Video(label="Input"), 
+    inference,
+    gr.inputs.Video(label="Input"),
     gr.outputs.Video(label="Output"),
     title=title,
     description=description,
     article=article,
     enable_queue=True,
-    examples=examples
-    ).launch(debug=True)
+    examples=examples,
+).launch(debug=True)

pexels-darina-belonogova-7539228.mp4

@@ -1,3 +0,0 @@
-version https://git-lfs.github.com/spec/v1
-oid sha256:54f4e572fa04e6c792d8dcdea9979c11265246ee0149c255d2d9a63b43642c48
-size 5885930

requirements.txt

@@ -1,6 +1,7 @@
-av==8.0.3
-torch==1.9.0
-torchvision==0.10.0
+av
+torch==2.1.0
+torchaudio==2.1.0
+torchvision==0.16.0
 tqdm==4.61.1
-pims==0.5
+pims
 gradio