Spaces:
Runtime error
Runtime error
File size: 3,300 Bytes
c1f7300 0e7cb07 d491e94 093967b 6810bbb c1f7300 0e7cb07 c1f7300 0e7cb07 6810bbb 0e7cb07 edc3608 0e7cb07 edc3608 0e7cb07 d491e94 0e7cb07 41394ac 0e7cb07 41394ac 0e7cb07 41394ac 0e7cb07 41394ac 0e7cb07 41394ac 0e7cb07 41394ac 035f115 41394ac 0e7cb07 035f115 41394ac 0e7cb07 41394ac 0e7cb07 41394ac 0e7cb07 41394ac |
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 sys
import subprocess
import time
from huggingface_hub import hf_hub_download
BASE_DIR = os.getcwd()
WEIGHTS_DIR = os.path.join(BASE_DIR, "weights")
OUTPUT_BASEPATH = os.path.join(BASE_DIR, "results-poor")
# Download specific files from Hugging Face repo
def download_checkpoints():
os.makedirs(WEIGHTS_DIR, exist_ok=True)
print("⬇️ Downloading necessary checkpoint files...")
try:
# Download FP8 checkpoint
checkpoint_fp8 = hf_hub_download(
repo_id="tencent/HunyuanVideo-Avatar",
filename="ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states_fp8.pt",
cache_dir=WEIGHTS_DIR,
local_dir=WEIGHTS_DIR,
local_dir_use_symlinks=False
)
# Download normal checkpoint for Flask/Gradio UI
checkpoint = hf_hub_download(
repo_id="tencent/HunyuanVideo-Avatar",
filename="ckpts/hunyuan-video-t2v-720p/transformers/mp_rank_00_model_states.pt",
cache_dir=WEIGHTS_DIR,
local_dir=WEIGHTS_DIR,
local_dir_use_symlinks=False
)
return checkpoint, checkpoint_fp8
except Exception as e:
print(f"❌ Error during checkpoint download: {e}")
sys.exit(1)
def run_sample_gpu_poor(checkpoint_fp8_path):
print("🎬 Running sample_gpu_poor.py...")
cmd = [
"python3", "hymm_sp/sample_gpu_poor.py",
"--input", "assets/test.csv",
"--ckpt", checkpoint_fp8_path,
"--sample-n-frames", "129",
"--seed", "128",
"--image-size", "704",
"--cfg-scale", "7.5",
"--infer-steps", "50",
"--use-deepcache", "1",
"--flow-shift-eval-video", "5.0",
"--save-path", OUTPUT_BASEPATH,
"--use-fp8",
"--cpu-offload",
"--infer-min"
]
env = os.environ.copy()
env["PYTHONPATH"] = "./"
env["MODEL_BASE"] = WEIGHTS_DIR
env["CPU_OFFLOAD"] = "1"
env["CUDA_VISIBLE_DEVICES"] = "0"
proc = subprocess.run(cmd, env=env)
if proc.returncode != 0:
print("❌ sample_gpu_poor.py failed.")
sys.exit(1)
print("✅ sample_gpu_poor.py completed successfully.")
def run_flask_audio(checkpoint_path):
print("🚀 Starting flask_audio.py...")
cmd = [
"torchrun",
"--nnodes=1",
"--nproc_per_node=1",
"--master_port=29605",
"hymm_gradio/flask_audio.py",
"--input", "assets/test.csv",
"--ckpt", checkpoint_path,
"--sample-n-frames", "129",
"--seed", "128",
"--image-size", "704",
"--cfg-scale", "7.5",
"--infer-steps", "50",
"--use-deepcache", "1",
"--flow-shift-eval-video", "5.0"
]
subprocess.Popen(cmd)
def run_gradio_ui():
print("🟢 Starting gradio_audio.py UI...")
cmd = ["python3", "hymm_gradio/gradio_audio.py"]
subprocess.Popen(cmd)
def main():
# Step 1: Download only needed files from Hugging Face repo
checkpoint, checkpoint_fp8 = download_checkpoints()
# Step 2: Run poor sample video generation
run_sample_gpu_poor(checkpoint_fp8)
# Step 3: Launch Flask + Gradio UIs
run_flask_audio(checkpoint)
time.sleep(5)
run_gradio_ui()
if __name__ == "__main__":
main()
|