Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
32520ec
1
Parent(s):
5313d97
time cacl
Browse files
app.py
CHANGED
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@@ -27,7 +27,7 @@ import datetime
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import shutil
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import tempfile
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import spaces
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-
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#* better for bg: logs/outs/train/remote/sft-T2SQNet_glassverse_cleargrasp_HISS_DREDS_DREDS_glassverse_interiorverse-4gpus-origin-lora128-1.3B-rgb_depth-w832-h480-Wan2.1-Fun-Control-2025-10-28-23:26:41/epoch-0-20000.safetensors
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@@ -148,7 +148,7 @@ def process_video(
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start_time = time.time()
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prediction_result = DKT_PIPELINE(
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@@ -165,6 +165,7 @@ def process_video(
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end_time = time.time()
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spend_time = end_time - start_time
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logger.info(f"DKT_PIPELINE spend time: {spend_time:.2f} seconds for depth prediction")
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@@ -180,6 +181,8 @@ def process_video(
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pc_end_time = time.time()
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pc_spend_time = pc_end_time - pc_start_time
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logger.info(f"prediction2pc_v2 spend time: {pc_spend_time:.2f} seconds for point cloud extraction")
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glb_files = []
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for idx, pcd in enumerate(pcds):
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@@ -196,6 +199,7 @@ def process_video(
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success = create_simple_glb_from_pointcloud(points, colors, glb_filename)
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if not success:
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logger.warning(f"Failed to save GLB file: {glb_filename}")
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glb_files.append(glb_filename)
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@@ -435,13 +439,14 @@ with gr.Blocks(css=css, title="DKT", head=head_html) as demo:
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return None, None, None, None, None, None, "Please upload a video file"
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try:
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start_time = time.time()
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output_path, glb_files = process_video(
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video_file, model_size, num_inference_steps, overlap
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)
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spend_time = time.time() - start_time
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logger.info(f"Total spend time in on_submit: {spend_time:.2f} seconds")
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if output_path is None:
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import shutil
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import tempfile
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import spaces
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import time
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#* better for bg: logs/outs/train/remote/sft-T2SQNet_glassverse_cleargrasp_HISS_DREDS_DREDS_glassverse_interiorverse-4gpus-origin-lora128-1.3B-rgb_depth-w832-h480-Wan2.1-Fun-Control-2025-10-28-23:26:41/epoch-0-20000.safetensors
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start_time = time.time()
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prediction_result = DKT_PIPELINE(
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end_time = time.time()
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spend_time = end_time - start_time
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logger.info(f"DKT_PIPELINE spend time: {spend_time:.2f} seconds for depth prediction")
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print(f"DKT_PIPELINE spend time: {spend_time:.2f} seconds for depth prediction")
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pc_end_time = time.time()
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pc_spend_time = pc_end_time - pc_start_time
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logger.info(f"prediction2pc_v2 spend time: {pc_spend_time:.2f} seconds for point cloud extraction")
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print(f"prediction2pc_v2 spend time: {pc_spend_time:.2f} seconds for point cloud extraction")
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glb_files = []
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for idx, pcd in enumerate(pcds):
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success = create_simple_glb_from_pointcloud(points, colors, glb_filename)
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if not success:
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logger.warning(f"Failed to save GLB file: {glb_filename}")
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print(f"Failed to save GLB file: {glb_filename}")
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glb_files.append(glb_filename)
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return None, None, None, None, None, None, "Please upload a video file"
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try:
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start_time = time.time()
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output_path, glb_files = process_video(
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video_file, model_size, num_inference_steps, overlap
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)
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spend_time = time.time() - start_time
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logger.info(f"Total spend time in on_submit: {spend_time:.2f} seconds")
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print(f"Total spend time in on_submit: {spend_time:.2f} seconds")
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if output_path is None:
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