Delete apps/gradio_app/new-inference.py

apps/gradio_app/new-inference.py

@@ -1,104 +0,0 @@
-import sys
-import os
-import subprocess
-from pathlib import Path
-import uuid
-import torch
-
-# Append the current directory to sys.path
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), '..')))
-
-def run_setup_script():
-    setup_script = os.path.join(os.path.dirname(__file__), "setup_scripts.py")
-    try:
-        result = subprocess.run(["python", setup_script], capture_output=True, text=True, check=True)
-        return result.stdout
-    except subprocess.CalledProcessError as e:
-        return f"Setup script failed: {e.stderr}"
-
-def run_inference(
-    model_path="./ckpts/zeroscope_v2_576w",
-    checkpoint_folder="./ckpts/zeroscope_v2_576w-Ghibli-LoRA",
-    prompt="Studio Ghibli style. Two women walk down coastal village path toward sea, passing colorful houses, sailboats visible.",
-    negative_prompt="ugly, noise, fragment, blur, static video",
-    width=256,
-    height=256,
-    num_frames=8,
-    num_steps=30,
-    guidance_scale=30.0,
-    fps=8,
-    lora_rank=32,
-    lora_scale=0.7,
-    noise_prior=0.1,
-    device="cuda",
-    seed=100
-):
-    print("Start Inference")
-    output_dir = "apps/gradio_app/temp_data"
-    os.makedirs(output_dir, exist_ok=True)
-
-    # Get list of files in output_dir
-    for file_name in os.listdir(output_dir):
-        # Check if file ends with .mp4
-        if file_name.endswith(".mp4"):
-            # Remove the file
-            os.remove(os.path.join(output_dir, file_name))
-
-    command = [
-        "python", "src/third_party/MotionDirector/main_inference.py",
-        "--model", model_path,
-        "--checkpoint_folder", checkpoint_folder,
-        "--prompt", prompt,
-        "--negative-prompt", negative_prompt,
-        "--width", str(width),
-        "--height", str(height),
-        "--num-frames", str(num_frames),
-        "--num-steps", str(num_steps),
-        "--guidance-scale", str(guidance_scale),
-        "--fps", str(fps),
-        "--lora_rank", str(lora_rank),
-        "--lora_scale", str(lora_scale),
-        "--noise_prior", str(noise_prior),
-        "--device", device,
-        "--seed", str(seed),
-        "--output_dir", output_dir,
-        "--no-prompt-name"
-    ]
-
-    # Use Popen to execute the command
-    process = subprocess.Popen(
-        command,
-        stdout=subprocess.PIPE,
-        stderr=subprocess.PIPE,
-        text=True,
-        bufsize=1  # Line buffering
-    )
-
-    # Read output line-by-line in real-time
-    output_lines = []
-    try:
-        for line in process.stdout:
-            output_lines.append(line.strip())
-    except Exception as e:
-        return None, f"Error reading output: {str(e)}"
-
-    # Capture stderr and wait for process to complete
-    stderr_output = process.communicate()[1]
-    if process.returncode != 0:
-        return None, f"Error: {stderr_output.strip()}"
-
-    # Check for MP4 files in output directory
-    output_file = [f for f in os.listdir(output_dir) if f.lower().endswith('.mp4')]
-    if output_file:
-        output_path = os.path.join(output_dir, output_file[-1])
-        if os.path.exists(output_path):
-            return output_path, "\n".join(output_lines)
-        else:
-            return None, f"Video file not found at {output_path}\nLogs:\n" + "\n".join(output_lines)
-    return None, f"No MP4 files found in {output_dir}\nLogs:\n" + "\n".join(output_lines)
-
-if __name__ == "__main__":
-    # Example usage
-    video_path, logs = run_inference(device="cpu" if not torch.cuda.is_available() else "cuda")
-    print(f"Generated Video: {video_path}")
-    print(f"Logs: {logs}")