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feat: windows infer & gradio (#312)

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* fix: windows infer

* docs: update readme

* docs: update readme

* feat: v1.5 gradio for windows&linux

* fix: dependencies

* feat: windows infer & gradio

---------

Co-authored-by: NeRF-Factory <zzhizhou66@gmail.com>
This commit is contained in:
Zhizhou Zhong
2025-04-12 23:22:22 +08:00
committed by GitHub
parent 36163fccbd
commit 67e7ee3c73
14 changed files with 613 additions and 245 deletions
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20
scripts/realtime_inference.py
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@@ -23,6 +23,15 @@ import shutil
import threading
import queue
import time
import subprocess
def fast_check_ffmpeg():
try:
subprocess.run(["ffmpeg", "-version"], capture_output=True, check=True)
return True
except:
return False
def video2imgs(vid_path, save_path, ext='.png', cut_frame=10000000):
@@ -318,7 +327,7 @@ if __name__ == "__main__":
parser.add_argument("--fps", type=int, default=25, help="Video frames per second")
parser.add_argument("--audio_padding_length_left", type=int, default=2, help="Left padding length for audio")
parser.add_argument("--audio_padding_length_right", type=int, default=2, help="Right padding length for audio")
parser.add_argument("--batch_size", type=int, default=25, help="Batch size for inference")
parser.add_argument("--batch_size", type=int, default=20, help="Batch size for inference")
parser.add_argument("--output_vid_name", type=str, default=None, help="Name of output video file")
parser.add_argument("--use_saved_coord", action="store_true", help='Use saved coordinates to save time')
parser.add_argument("--saved_coord", action="store_true", help='Save coordinates for future use')
@@ -332,6 +341,15 @@ if __name__ == "__main__":
args = parser.parse_args()
# Configure ffmpeg path
if not fast_check_ffmpeg():
print("Adding ffmpeg to PATH")
# Choose path separator based on operating system
path_separator = ';' if sys.platform == 'win32' else ':'
os.environ["PATH"] = f"{args.ffmpeg_path}{path_separator}{os.environ['PATH']}"
if not fast_check_ffmpeg():
print("Warning: Unable to find ffmpeg, please ensure ffmpeg is properly installed")
# Set computing device
device = torch.device(f"cuda:{args.gpu_id}" if torch.cuda.is_available() else "cpu")