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#!/usr/bin/env python3
import os
import sys
import subprocess
import gradio as gr
import torch
sys.path.insert(0, '/app/FunGen')
def process_video(video, mode, overwrite, autotune):
"""Process video with FunGen"""
print(f"[DEBUG] Called with video={video}, mode={mode}, overwrite={overwrite}, autotune={autotune}")
if video is None:
return "❌ No video uploaded", None
try:
input_path = video
print(f"[DEBUG] Input path: {input_path}")
if not os.path.exists(input_path):
return f"❌ File not found: {input_path}", None
file_size_mb = os.path.getsize(input_path) / (1024**2)
status = f"🚀 Processing: {os.path.basename(input_path)}\n"
status += f"📁 Size: {file_size_mb:.1f} MB\n"
status += f"⚙️ Mode: {mode}\n"
status += f"⏳ Starting...\n\n"
print(f"[DEBUG] Status: {status}")
# Build command without fake flags
cmd = ["python", "/app/FunGen/main.py", input_path, "--mode", mode]
if overwrite:
cmd.append("--overwrite")
if not autotune:
cmd.append("--no-autotune")
print(f"[DEBUG] Command: {' '.join(cmd)}")
# Set environment
env = os.environ.copy()
result = subprocess.run(cmd, cwd="/app/FunGen", capture_output=True, text=True, timeout=3600, env=env)
print(f"[DEBUG] Return code: {result.returncode}")
print(f"[DEBUG] STDOUT:\n{result.stdout}")
print(f"[DEBUG] STDERR:\n{result.stderr}")
# Look for output - FunGen saves relative to input or in current directory
output_file = None
search_paths = [
os.path.dirname(input_path), # Same folder as input
"/app/FunGen",
"/tmp/outputs",
os.getcwd()
]
for search_path in search_paths:
if os.path.exists(search_path):
print(f"[DEBUG] Searching: {search_path}")
for root, dirs, files in os.walk(search_path):
for f in files:
print(f"[DEBUG] Found file: {os.path.join(root, f)}")
if f.endswith(".funscript") and not f.endswith(".roll.funscript"):
output_file = os.path.join(root, f)
print(f"[DEBUG] ✓ Matched funscript: {output_file}")
break
if output_file:
break
if output_file:
break
if output_file and os.path.exists(output_file):
status += f"✅ Complete!\n📜 {os.path.basename(output_file)}"
print(f"[DEBUG] Returning: {output_file}")
return status, output_file
# Not found - show the full output for debugging
status += f"⚠️ No output generated\n\nFull Output:\n{result.stdout}\n\nErrors:\n{result.stderr}"
return status, None
except Exception as e:
error = f"❌ Exception: {str(e)}"
print(f"[DEBUG] Exception: {error}")
import traceback
print(traceback.format_exc())
return error, None
with gr.Blocks(title="FunGen") as demo:
gr.Markdown("# 🎬 FunGen - Funscript Generator")
with gr.Row():
gpu_info = "✅ GPU Available" if torch.cuda.is_available() else "❌ No GPU"
gr.Textbox(value=gpu_info, label="Status", interactive=False)
with gr.Row():
with gr.Column():
video_input = gr.File(label="Upload Video", file_types=["video"], type="filepath")
mode_input = gr.Dropdown(
["Hybrid Intelligence Tracker", "Oscillation Detector (Legacy)", "YOLO ROI Tracker"],
value="Hybrid Intelligence Tracker",
label="Mode"
)
overwrite_input = gr.Checkbox(label="Overwrite", value=False)
autotune_input = gr.Checkbox(label="Apply Autotune", value=True)
process_btn = gr.Button("Process Video", variant="primary")
with gr.Column():
status_output = gr.Textbox(label="Status", lines=10, interactive=False)
file_output = gr.File(label="Download", interactive=False)
process_btn.click(
fn=process_video,
inputs=[video_input, mode_input, overwrite_input, autotune_input],
outputs=[status_output, file_output]
)
if __name__ == "__main__":
demo.queue().launch(server_name="0.0.0.0", server_port=7860, show_error=True)
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