nan
e7aeeb21d4
- Implement sync_models.py for preparing and uploading ONNX artifacts. - Create build_node.py for building and validating Blender scripts. - Add docs.py for building and previewing documentation with Mike or MkDocs. - Introduce model_exports.py for exporting PyTorch models to ONNX format. - Develop pack.py for packaging the project with dependencies for different platforms. - Add test_sync_models.py to validate sync_models functionality. - Add test_tool_commands.py to ensure repository tools have correct command scripts. - Initialize tools package with __init__.py.
81 lines
2.9 KiB
Python
81 lines
2.9 KiB
Python
"""Load and scale Depth file artifacts shared by Blender workflows."""
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import json
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from pathlib import Path
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import bpy
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from .image_data import depth_data_name, image_empty_bounds
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def load_depth_metadata(path):
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"""Read and validate the compact camera metadata beside a Depth texture."""
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metadata = json.loads(Path(path).read_text(encoding="utf-8"))
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try:
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image_size = tuple(int(value) for value in metadata["image_size"])
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intrinsics = tuple(
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tuple(float(value) for value in row)
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for row in metadata["intrinsics"]
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)
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reference_depth = float(metadata["reference_depth"])
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except (KeyError, TypeError, ValueError) as error:
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raise ValueError("Depth metadata is invalid") from error
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if (
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len(image_size) != 2
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or min(image_size) <= 0
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or len(intrinsics) != 3
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or any(len(row) != 3 for row in intrinsics)
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or intrinsics[0][0] <= 0.0
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or intrinsics[1][1] <= 0.0
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or reference_depth <= 0.0
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):
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raise ValueError("Depth metadata is invalid")
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return {
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"image_size": image_size,
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"intrinsics": intrinsics,
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"reference_depth": reference_depth,
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}
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def load_depth_result_image(path, source_object, metadata):
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"""Load, validate, name, configure, and pack a generated Depth texture."""
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image = bpy.data.images.load(str(path), check_existing=False)
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try:
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if tuple(int(value) for value in image.size) != metadata["image_size"]:
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raise ValueError("Depth texture dimensions do not match its metadata")
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image.name = depth_data_name(source_object)
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image.colorspace_settings.name = "Non-Color"
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image.alpha_mode = "CHANNEL_PACKED"
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image.pack()
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return image
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except Exception:
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bpy.data.images.remove(image, do_unlink=True)
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raise
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def camera_depth_values(image):
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"""Return top-down camera Z and validity from a loaded Depth texture."""
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import numpy as np
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width, height = (int(value) for value in image.size)
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pixels = np.empty(width * height * 4, dtype=np.float32)
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image.pixels.foreach_get(pixels)
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pixels = np.flipud(pixels.reshape((height, width, 4)))
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return pixels[..., 2], pixels[..., 3] > 0.5
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def depth_uniform_scale(source_object, metadata, bounds=None):
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"""Convert model camera units uniformly into Image Empty local distance."""
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import numpy as np
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intrinsics = metadata["intrinsics"]
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width, height = metadata["image_size"]
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reference_depth = metadata["reference_depth"]
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x_min, x_max, y_min, y_max = bounds or image_empty_bounds(source_object)
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plane_width = x_max - x_min
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plane_height = y_max - y_min
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fx, fy = float(intrinsics[0][0]), float(intrinsics[1][1])
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scale_x = plane_width * fx / (max(width - 1, 1) * reference_depth)
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scale_y = plane_height * fy / (max(height - 1, 1) * reference_depth)
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return float(np.sqrt(scale_x * scale_y))
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