Add files using upload-large-folder tool

.vscode/launch.json

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+{
+    // 使用 IntelliSense 了解相关属性。 
+    // 悬停以查看现有属性的描述。
+    // 欲了解更多信息，请访问: https://go.microsoft.com/fwlink/?linkid=830387
+    "version": "0.2.0",
+    "configurations": []
+}

00777c41d4/scene_iphone_metadata.npz

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00a231a370/scene_iphone_metadata.npz

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00dd871005/scene_iphone_metadata.npz

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01ce24e652/scene_iphone_metadata.npz

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027cd6ea0f/scene_iphone_metadata.npz

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02c2ddee2a/scene_iphone_metadata.npz

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033d0b9343/scene_iphone_metadata.npz

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036bce3393/scene_dslr_metadata.npz

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0452249a1e/scene_iphone_metadata.npz

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04c23ccd1d/scene_iphone_metadata.npz

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04df8734b7/scene_iphone_metadata.npz

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052d72e137/scene_iphone_metadata.npz

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053a94cf68/scene_iphone_metadata.npz

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05d3c8c6f0/scene_iphone_metadata.npz

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062e5a23a6/scene_iphone_metadata.npz

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06bd2cf800/scene_iphone_metadata.npz

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0796447f4b/scene_iphone_metadata.npz

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079a326597/scene_dslr_metadata.npz

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07e6f56969/scene_iphone_metadata.npz

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07f5b601ee/scene_dslr_metadata.npz

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086f09d6e3/scene_iphone_metadata.npz

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08bbbdcc3d/scene_dslr_metadata.npz

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delete_tmp.py

@@ -0,0 +1,21 @@
+import os
+
+def delete_tmp_npy(root_dir="."):
+    """
+    遍历 root_dir 下所有文件，删除以 `.tmp.npy` 结尾的残留文件
+    """
+    deleted = 0
+    for dirpath, _, filenames in os.walk(root_dir):
+        for file in filenames:
+            if file.endswith(".tmp.npy"):
+                full_path = os.path.join(dirpath, file)
+                try:
+                    os.remove(full_path)
+                    print(f"🗑️ 删除: {full_path}")
+                    deleted += 1
+                except Exception as e:
+                    print(f"❌ 删除失败: {full_path}, 原因: {e}")
+    print(f"\n完成清理，共删除 {deleted} 个 .tmp.npy 文件")
+
+if __name__ == "__main__":
+    delete_tmp_npy(".")

error_scenes.txt

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+00a231a370 [Errno 2] No such file or directory: '/mnt/juicefs/datasets/vanilla_scannetpp/scannetpp_v2/data/00a231a370/iphone/rgb_masks/frame_006050.png'
+00dd871005 [Errno 2] No such file or directory: '/mnt/juicefs/datasets/vanilla_scannetpp/scannetpp_v2/data/00dd871005/iphone/rgb_masks/frame_000040.png'
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+00a231a370 [Errno 2] No such file or directory: '/mnt/juicefs/datasets/vanilla_scannetpp/scannetpp_v2/data/00a231a370/iphone/rgb_masks/frame_006050.png'
+00dd871005 [Errno 2] No such file or directory: '/mnt/juicefs/datasets/vanilla_scannetpp/scannetpp_v2/data/00dd871005/iphone/rgb_masks/frame_000040.png'
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c startswith first arg must be bytes or a tuple of bytes, not str
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], dtype=float32),
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)
+c29b5e479c No module named 'fast_simplification'
+c29b5e479c You may specify ``target_reduction`` or ``target_count``, but not both
+c29b5e479c Trimesh.simplify_quadric_decimation() got an unexpected keyword argument 'target_count'
+c29b5e479c ``target_reduction`` must be between 0 and 1
+c29b5e479c You may specify ``target_reduction`` or ``target_count``, but not both
+c29b5e479c ``target_reduction`` must be between 0 and 1
+c29b5e479c name 'pyrender_scene' is not defined
+c29b5e479c GLError(
+	err = 1281,
+	description = b'invalid value',
+	baseOperation = glBufferData,
+	pyArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArgs = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	),
+	cArguments = (
+		GL_ARRAY_BUFFER,
+		3278864160,
+		array([1.4931395 , 9.968557  , 5.0007644 , ..., 0.65882355, 0.8901961 ,
+       1.        ], shape=(819716040,), dtype...,
+		GL_STATIC_DRAW,
+	)
+)

pth_2_npy.py

@@ -0,0 +1,273 @@
+import os
+import sys
+import numpy as np
+import torch
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from functools import partial
+from collections import deque
+from tqdm import tqdm
+
+# 用 imageio 保存 PNG（支持 8/16 bit）
+import imageio.v2 as imageio
+
+def _register_torch_safe_globals():
+    """
+    兼容老的 .pth：torch>=2.6 在 weights_only/安全反序列化下，
+    一些历史 .pth 会引用 numpy 的内部对象（如 numpy.core.multiarray._reconstruct）。
+    这里把这些对象加入 torch 的安全白名单后再重试加载。
+    """
+    try:
+        from torch.serialization import add_safe_globals
+    except Exception:
+        return
+    import importlib
+    candidates = []
+    for dotted in (
+        "numpy.core.multiarray._reconstruct",
+        "numpy._core.multiarray._reconstruct",
+    ):
+        try:
+            mod_path, attr = dotted.rsplit(".", 1)
+            mod = importlib.import_module(mod_path)
+            obj = getattr(mod, attr, None)
+            if obj is not None:
+                candidates.append(obj)
+        except Exception:
+            pass
+    if candidates:
+        try:
+            add_safe_globals(candidates)
+        except Exception:
+            pass
+
+def extract_array(obj):
+    """从 pth 中提取 numpy 数组（tensor / ndarray / dict / list）"""
+    if isinstance(obj, torch.Tensor):
+        return obj.detach().cpu().numpy()
+    elif isinstance(obj, np.ndarray):
+        return obj
+    elif isinstance(obj, dict):
+        for v in obj.values():
+            arr = extract_array(v)
+            if arr is not None:
+                return arr
+    elif isinstance(obj, (list, tuple)):
+        items = [extract_array(x) for x in obj]
+        try:
+            if all(isinstance(x, np.ndarray) for x in items if x is not None):
+                return np.stack(items)
+        except Exception:
+            pass
+        return np.array(items, dtype=object)
+    return None
+
+def _to_hw_or_hwc(arr: np.ndarray) -> np.ndarray:
+    """
+    尽量把任意形状的数组转成 HxW 或 HxWxC 以便存 PNG。
+    规则：
+      - 去掉所有长度为1的维度（squeeze）
+      - (C,H,W) -> (H,W,C)
+      - (H,W,1) -> (H,W)
+      - 前面都不满足：如果维度>3，优先取前面的第一个切片直到<=3维
+    """
+    a = np.array(arr)  # 拷贝一层引用
+    # 先 squeeze
+    a = np.squeeze(a)
+    # 若仍然超过3维，逐步取第0索引切片直到<=3维
+    while a.ndim > 3:
+        a = a[0]
+        a = np.squeeze(a)
+    # (C,H,W) -> (H,W,C)
+    if a.ndim == 3 and a.shape[0] in (1, 3):
+        a = np.transpose(a, (1, 2, 0))
+    # (H,W,1) -> (H,W)
+    if a.ndim == 3 and a.shape[2] == 1:
+        a = a[:, :, 0]
+    # 最终只接受 2D 或 3D(HWC)；否则再硬切
+    if a.ndim == 0:
+        a = a.reshape(1, 1)
+    elif a.ndim == 1:
+        # 1D 转成“条形图”
+        a = a.reshape(1, -1)
+    return a
+
+def _to_png_dtype(a: np.ndarray) -> (np.ndarray, str):
+    """
+    将任意数值数组转为 PNG 友好 dtype：
+      - 若是整数：
+          * max<=255 -> uint8
+          * max<=65535 -> uint16（单通道/多通道 imageio 通常也能写）
+          * 其余 -> clip 到 16位并转 uint16
+      - 若是浮点：
+          * 若 min>=0 且 max<=1 -> 直接 0..1 线性放大为 0..255 uint8
+          * 否则 min/max 归一化到 0..255（全常数则全0）
+      - 若是 bool -> uint8(0/255)
+    返回：(数组, '8bit' or '16bit')
+    """
+    a = np.asarray(a)
+
+    # 布尔
+    if a.dtype == np.bool_:
+        return (a.astype(np.uint8) * 255, "8bit")
+
+    # 整数
+    if np.issubdtype(a.dtype, np.integer):
+        maxv = int(a.max()) if a.size else 0
+        minv = int(a.min()) if a.size else 0
+        if maxv <= 65535 and minv >= 0:
+            return (a.astype(np.uint16), "16bit")
+        else:
+            # 夹到 [0, 65535] 再转 16bit
+            a = np.clip(a, 0, 65535).astype(np.uint16)
+            return (a, "16bit")
+
+    # 其他类型，转 uint8（尽力而为）
+    return (a.astype(np.uint8, copy=False), "16bit")
+
+def _pth_to_png_path(pth_path: str) -> str:
+    """
+    将 .../frame_XXXXX.jpg.pth -> .../frame_XXXXX.png
+    其他 .../xxx.pth -> .../xxx.png
+    """
+    base = os.path.splitext(pth_path)[0]  # 去掉 .pth
+    # 去掉 .jpg / .jpeg 尾巴
+    for ext in (".jpg", ".jpeg", ".JPG", ".JPEG"):
+        if base.endswith(ext):
+            base = base[: -len(ext)]
+            break
+    return base + ".png"
+
+def process_one_to_png(pth_path: str, overwrite: bool, weights_only: bool):
+    """
+    子进程：加载 pth -> 提取 -> 保存 PNG（直接保存在源目录，命名同上）
+    """
+    try:
+        png_path = _pth_to_png_path(pth_path)
+        if (not overwrite) and os.path.exists(png_path):
+            return (pth_path, png_path, "skip-exist", None)
+
+        # 加载 .pth（兼容处理）
+        try:
+            data = torch.load(pth_path, map_location="cpu", weights_only=weights_only)
+        except TypeError:
+            data = torch.load(pth_path, map_location="cpu")
+        except Exception as e1:
+            _register_torch_safe_globals()
+            try:
+                data = torch.load(pth_path, map_location="cpu", weights_only=False)
+            except Exception as e2:
+                return (pth_path, png_path, "fail", f"{type(e1).__name__}: {e1} | fallback: {type(e2).__name__}: {e2}")
+
+        arr = extract_array(data)
+        if arr is None:
+            return (pth_path, png_path, "no-array", None)
+
+        # 变成可保存的 HxW 或 HxWxC
+        img = _to_hw_or_hwc(arr)
+        # 转到 8bit/16bit 合理类型
+        img, bit = _to_png_dtype(img)
+
+        # 确保目录存在（一般是原目录，稳妥起见保留）
+        os.makedirs(os.path.dirname(png_path) or ".", exist_ok=True)
+
+        # 保存 PNG
+        imageio.imwrite(png_path, img)
+
+        shape_info = img.shape if hasattr(img, "shape") else None
+        return (pth_path, png_path, "ok", f"{shape_info}, {bit}")
+    except Exception as e:
+        return (pth_path, "", "fail", str(e))
+
+def collect_pth_files(root_dir="."):
+    """
+    收集所有 obj_ids 目录下的 *.pth（直接在源目录保存 PNG）
+    """
+    paths = []
+    for dirpath, dirnames, filenames in os.walk(root_dir):
+        if os.path.basename(dirpath) == "refined_ins_ids":
+            for file in filenames:
+                if file.endswith(".pth"):
+                    paths.append(os.path.join(dirpath, file))
+    return paths
+
+if __name__ == "__main__":
+    root_dir = "."
+    max_workers = max(1, os.cpu_count() // 2)   # 并发进程数
+    inflight_factor = 8                          # 每个进程的在飞任务基数
+    max_inflight = max_workers * inflight_factor
+    weights_only = False                         # 兼容性优先；如需更安全可设 True
+    overwrite = False                            # 不覆盖已存在 PNG
+
+    pth_list = collect_pth_files(root_dir)
+    if not pth_list:
+        print("未找到任何 obj_ids/*.pth 任务")
+        sys.exit(0)
+
+    # 预过滤：跳过已存在 PNG
+    pending = []
+    pre_skipped = 0
+    for p in pth_list:
+        target = _pth_to_png_path(p)
+        if (not overwrite) and os.path.exists(target):
+            pre_skipped += 1
+        else:
+            pending.append(p)
+
+    if not pending:
+        print(f"全部已存在 PNG，无需处理（共 {len(pth_list)} 个，预跳过 {pre_skipped} 个）。")
+        sys.exit(0)
+
+    print(f"共 {len(pth_list)} 个 .pth，其中待处理 {len(pending)} 个，预跳过 {pre_skipped} 个；"
+          f"使用 {max_workers} 个进程并行转换…")
+    # 展示前 5 个待处理任务
+    preview = 5
+    for i, pp in enumerate(pending[:preview], 1):
+        print(f"  [{i}] {pp}  ->  {_pth_to_png_path(pp)}")
+    if len(pending) > preview:
+        print(f"  ... 其余 {len(pending)-preview} 个略")
+
+    fn = partial(process_one_to_png, overwrite=overwrite, weights_only=weights_only)
+
+    ok = skip = fail = noarr = 0
+    task_queue = deque(pending)
+    inflight = set()
+
+    with ProcessPoolExecutor(max_workers=max_workers) as ex, tqdm(total=len(pending), desc="Converting to PNG", smoothing=0.1) as pbar:
+        # 先填满在飞
+        while task_queue and len(inflight) < max_inflight:
+            fut = ex.submit(fn, task_queue.popleft())
+            inflight.add(fut)
+
+        while inflight:
+            done = []
+            for fut in as_completed(inflight, timeout=None):
+                done.append(fut)
+                try:
+                    pth_path, png_path, status, info = fut.result()
+                    if status == "ok":
+                        ok += 1
+                        print(f"✅ 转换成功: {pth_path} -> {png_path}  {info}", flush=True)
+                    elif status == "skip-exist":
+                        skip += 1
+                        print(f"⏭️ 已存在，跳过: {pth_path}", flush=True)
+                    elif status == "no-array":
+                        noarr += 1
+                        print(f"⚠️ 无可转换数组: {pth_path}", flush=True)
+                    else:
+                        fail += 1
+                        print(f"❌ 失败: {pth_path}\n   原因: {info}", flush=True)
+                except Exception as e:
+                    fail += 1
+                    print(f"❌ 失败(执行期异常): {e}", flush=True)
+                finally:
+                    pbar.update(1)
+
+                # 补充新的任务
+                if task_queue:
+                    fut_new = ex.submit(fn, task_queue.popleft())
+                    inflight.add(fut_new)
+
+            for f in done:
+                inflight.discard(f)
+
+    print(f"\n完成。成功 {ok}，预跳过 {pre_skipped}，运行中跳过 {skip}，无数组 {noarr}，失败 {fail}")

read_npy.py

@@ -0,0 +1,46 @@
+#!/usr/bin/env python3
+# save as pth2png_raw.py
+import argparse
+import numpy as np
+import torch
+import imageio.v3 as iio
+
+def main():
+    ap = argparse.ArgumentParser(description="Convert 2D .pth matrix to uint16 PNG (no scaling)")
+    ap.add_argument("--input_pth", help=".pth 文件路径",default="0a5c013435/refined_ins_ids/frame_000000.jpg.pth")
+    ap.add_argument("--output_png", help="输出 PNG 路径",default="out_png/frame_000000.jpg.png")
+    ap.add_argument("--key", help="当 .pth 是字典时，指定键名")
+    ap.add_argument("--clip", action="store_true",
+                    help="可选：仅做区间裁剪到 [0, 65535]，不缩放")
+    args = ap.parse_args()
+
+    obj = torch.load(args.input_pth, map_location="cpu")
+    if args.key is not None:
+        obj = obj[args.key]
+
+    if isinstance(obj, torch.Tensor):
+        arr = obj.detach().cpu().numpy()
+    else:
+        arr = np.array(obj)
+
+    arr = np.squeeze(arr)
+    if arr.ndim != 2:
+        raise ValueError(f"期望二维矩阵，实际为 {arr.shape}")
+
+    # 处理 NaN/Inf → 0（不属于缩放）
+    bad = ~np.isfinite(arr)
+    if bad.any():
+        arr = np.where(bad, 0, arr)
+
+    # 可选：只裁剪到合法的 uint16 区间，避免溢出回绕（仍不做缩放）
+    if args.clip:
+        arr = np.clip(arr, 0, 65535)
+
+    # 仅类型转换为 uint16（不缩放）
+    u16 = arr.astype(np.uint16)
+
+    # 保存为 16-bit 灰度 PNG
+    iio.imwrite(args.output_png, u16)
+
+if __name__ == "__main__":
+    main()

read_png.py

@@ -0,0 +1,11 @@
+from PIL import Image
+import numpy as np
+
+# 打开 PNG 文件
+img = Image.open("out_png/frame_000000.jpg.png")
+
+# 转换为 numpy 数组
+arr = np.array(img)
+
+print(arr.shape, arr.dtype)
+print(arr)

remove_files.py

@@ -0,0 +1,20 @@
+import os
+import shutil
+
+def remove_obj_ids_npy(root_dir="."):
+    """
+    递归删除 root_dir 下所有 obj_ids_npy 文件夹
+    """
+    for dirpath, dirnames, filenames in os.walk(root_dir, topdown=False):
+        for dirname in dirnames:
+            if dirname == "obj_ids":
+                target = os.path.join(dirpath, dirname)
+                try:
+                    shutil.rmtree(target)
+                    print(f"🗑️ 已删除: {target}")
+                except Exception as e:
+                    print(f"⚠️ 删除失败 {target}: {e}")
+
+if __name__ == "__main__":
+    root_dir = "."   # 可以改成你的根目录路径
+    remove_obj_ids_npy(root_dir)

splits/1.txt

@@ -0,0 +1,40 @@
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splits/2.txt

@@ -0,0 +1,40 @@
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splits/3.txt

@@ -0,0 +1,40 @@
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splits/4.txt

@@ -0,0 +1,40 @@
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splits/5.txt

@@ -0,0 +1,40 @@
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splits/6.txt

@@ -0,0 +1,40 @@
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splits/7.txt

@@ -0,0 +1,40 @@
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splits/nvs_sem_train.txt

@@ -0,0 +1,230 @@
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splits/nvs_sem_val.txt

@@ -0,0 +1,50 @@
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splits/nvs_test.txt

@@ -0,0 +1,50 @@
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splits/sem_test.txt

@@ -0,0 +1,50 @@
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splits/splits.py

@@ -0,0 +1,30 @@
+from pathlib import Path
+
+# 输入文件路径
+train_file = Path("/mnt/juicefs/datasets/vanilla_scannetpp/splits/nvs_sem_train.txt")
+val_file = Path("/mnt/juicefs/datasets/vanilla_scannetpp/splits/nvs_sem_val.txt")
+
+# 读取两个文件内容
+with open(train_file, "r") as f:
+    train_ids = [line.strip() for line in f if line.strip()]
+
+with open(val_file, "r") as f:
+    val_ids = [line.strip() for line in f if line.strip()]
+
+# 合并并去重
+all_ids = sorted(set(train_ids + val_ids))
+
+# 分成 7 份
+chunks = [[] for _ in range(7)]
+for idx, scene_id in enumerate(all_ids):
+    chunks[idx % 7].append(scene_id)
+
+# 输出保存为 1.txt 到 7.txt
+output_dir = Path("/mnt/juicefs/datasets/vanilla_scannetpp/splits")
+output_dir.mkdir(parents=True, exist_ok=True)
+
+for i, chunk in enumerate(chunks):
+    with open(output_dir / f"{i+1}.txt", "w") as f:
+        f.write("\n".join(chunk) + "\n")
+
+print(f"✅ Done. Saved {len(all_ids)} scenes into 7 files in {output_dir}")