""" load_examples.py — quickstart for the SMAL dog dataset. Shows how to read the library (poses / shapes / textures) and how to stream a render shard (rgb + npz) without unpacking it. Run from the repo root: python scripts/load_examples.py """ import io import os import glob import tarfile import numpy as np REPO = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) LIB = os.path.join(REPO, "library") OUTPUTS = os.path.join(REPO, "outputs") def show_library(): poses = np.load(os.path.join(LIB, "poses", "poses.npz")) print("poses.npz:") print(" pose_6d", poses["pose_6d"].shape, poses["pose_6d"].dtype, " # (N, 34 joints, 6D rot)") shapes = np.load(os.path.join(LIB, "shapes", "shapes.npz"), allow_pickle=True) print("shapes.npz:") for k in ["beta", "betas_limbs", "pose_6d"]: print(f" {k}", shapes[k].shape, shapes[k].dtype) print(" logscale_part_list", list(shapes["logscale_part_list"])) tex = sorted(glob.glob(os.path.join(LIB, "textures", "texture_*.png"))) has_atlas = os.path.exists(os.path.join(LIB, "textures", "uv_atlas.pth")) print(f"textures: {len(tex)} PNGs (2048^2) + single shared uv_atlas.pth " f"({'present' if has_atlas else 'MISSING'})") def stream_one_render(): shards = sorted(glob.glob(os.path.join(OUTPUTS, "shard_*.tar"))) if not shards: print("\n(no render shards present — download outputs/ to try this)") return print(f"\nstreaming first sample from {os.path.basename(shards[0])}:") with tarfile.open(shards[0], "r") as tar: members = tar.getmembers() rgb = next(m for m in members if m.name.endswith("/rgb/00.png")) pose = rgb.name.split("/")[0] # pose_NNNNNN npz_m = tar.getmember(f"{pose}/npz/00.npz") data = np.load(io.BytesIO(tar.extractfile(npz_m).read()), allow_pickle=True) png_bytes = tar.extractfile(rgb).read() print(f" {pose} rgb {len(png_bytes)} bytes, npz keys: {sorted(data.files)}") print(" npz pose_6d", data["smal/pose_6d"].shape, "| keyp_2d_all", data["smal/keyp_2d_all"].shape, "| model", str(data["smal/smal_model_type"])) if __name__ == "__main__": show_library() stream_one_render()