Revert "more logs to find missing fbx"
Browse filesThis reverts commit 83e054a1f07fc68fde59fb62900a7bed5d0b1bc0.
- app.py +0 -1
- src/system/ar.py +2 -11
app.py
CHANGED
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@@ -192,7 +192,6 @@ def run_inference_python(
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writer_config['output_dir'] = str(Path(output_file).parent)
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writer_config['output_name'] = Path(output_file).name
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writer_config['user_mode'] = False # Enable NPZ export for skeleton
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-
print(f"Writer config for skeleton: {writer_config}")
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else: # skin
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writer_config['npz_dir'] = str(skeleton_npz_dir)
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writer_config['output_name'] = str(output_file)
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writer_config['output_dir'] = str(Path(output_file).parent)
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writer_config['output_name'] = Path(output_file).name
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writer_config['user_mode'] = False # Enable NPZ export for skeleton
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else: # skin
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writer_config['npz_dir'] = str(skeleton_npz_dir)
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writer_config['output_name'] = str(output_file)
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src/system/ar.py
CHANGED
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@@ -88,11 +88,9 @@ class ARWriter(BasePredictionWriter):
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trainer.predict_loop.run()
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def write_on_batch_end(self, trainer, pl_module: ARSystem, prediction: List[Dict], batch_indices, batch, batch_idx, dataloader_idx):
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print(f"ARWriter.write_on_batch_end called with {len(prediction)} predictions")
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assert 'path' in batch
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paths = batch['path']
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detokenize_output_list: List[DetokenizeOutput] = prediction
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print(f"Processing {len(detokenize_output_list)} detokenize outputs")
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vertices = batch['vertices']
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origin_vertices = batch['origin_vertices']
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@@ -116,7 +114,6 @@ class ARWriter(BasePredictionWriter):
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num_faces = num_faces.detach().cpu().numpy()
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for (id, detokenize_output) in enumerate(detokenize_output_list):
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print(f"Processing detokenize output {id}: {type(detokenize_output)}")
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assert isinstance(detokenize_output, DetokenizeOutput), f"expect item of the list to be DetokenizeOutput, found: {type(detokenize_output)}"
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def make_path(save_name: str, suffix: str, trim: bool=False):
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if trim:
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@@ -160,15 +157,9 @@ class ARWriter(BasePredictionWriter):
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raw_data.export_pc(path=make_path(self.export_pc, 'obj'))
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if self.export_fbx is not None:
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if not self.user_mode:
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-
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print(f"ARWriter: Exporting FBX to {fbx_path}")
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raw_data.export_fbx(path=fbx_path)
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print(f"ARWriter: FBX export completed for {fbx_path}")
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else:
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if self.output_name is not None:
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print(f"ARWriter: Exporting FBX to {self.output_name} (user mode)")
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raw_data.export_fbx(path=self.output_name)
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else:
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-
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print(f"ARWriter: Exporting FBX to {fbx_path} (user mode, trim)")
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raw_data.export_fbx(path=fbx_path)
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trainer.predict_loop.run()
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def write_on_batch_end(self, trainer, pl_module: ARSystem, prediction: List[Dict], batch_indices, batch, batch_idx, dataloader_idx):
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assert 'path' in batch
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paths = batch['path']
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detokenize_output_list: List[DetokenizeOutput] = prediction
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vertices = batch['vertices']
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origin_vertices = batch['origin_vertices']
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num_faces = num_faces.detach().cpu().numpy()
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for (id, detokenize_output) in enumerate(detokenize_output_list):
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assert isinstance(detokenize_output, DetokenizeOutput), f"expect item of the list to be DetokenizeOutput, found: {type(detokenize_output)}"
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def make_path(save_name: str, suffix: str, trim: bool=False):
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if trim:
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raw_data.export_pc(path=make_path(self.export_pc, 'obj'))
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if self.export_fbx is not None:
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if not self.user_mode:
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+
raw_data.export_fbx(path=make_path(self.export_fbx, 'fbx'))
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else:
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if self.output_name is not None:
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raw_data.export_fbx(path=self.output_name)
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else:
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+
raw_data.export_fbx(path=make_path(self.export_fbx, 'fbx', trim=True))
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