【Hackathon 5th No.68】轻量语义分割网络PIDNet #3548

flytocc · 2023-10-29T03:27:20Z

PR types

New features

PR changes

Task PaddlePaddle/Paddle#57262
RPC PaddlePaddle/community#722

Description

添加了PIDNet网络
新增了一种edge生成方法 AddEdgeLabel transform
修复了 CrossEntropyLoss 的一个bug
为OhemCrossEntropyLoss增加了对 weight 的支持

used AI Studio for training. Thanks a lot!

paddle-bot · 2023-10-29T03:27:24Z

Thanks for your contribution!

shiyutang

感谢贡献，1. 有一些细节问题，同时2. 需要在configs目录下补充readme；另外3. 辛苦确认训练参数、transform等配置，如果确认，我们在我们这边进行训练。（4. 训练之前可以提供下backbone的预训练权重。）

configs/pidnet/pidnet_s_cityscapes_1024x1024_120k.yml

paddleseg/models/backbones/pidnet.py

paddleseg/models/losses/cross_entropy_loss.py

paddleseg/models/losses/ohem_cross_entropy_loss.py

paddleseg/transforms/transforms.py

flytocc · 2023-10-30T14:26:53Z

这里是imagenet_pretrained weights和2xb6-120k_1024x1024-cityscapes weights

百度网盘

shiyutang · 2023-11-01T08:29:13Z

这里是imagenet_pretrained weights和2xb6-120k_1024x1024-cityscapes weights

百度网盘

flytocc · 2023-11-01T08:32:27Z

这里是imagenet_pretrained weights和2xb6-120k_1024x1024-cityscapes weights
百度网盘

现在应该有了

shiyutang

模型权重有点问题，你重新给我提交下吧，我把链接给你～

shiyutang · 2023-11-01T08:40:00Z

paddleseg/transforms/transforms.py

+        kernel = np.ones((self.edge_size, self.edge_size), np.uint8)
+        edge = np.pad(
+            edge[self.y_k_size:-self.y_k_size, self.x_k_size:-self.x_k_size],
+            ((self.y_k_size, self.y_k_size), (self.x_k_size, self.x_k_size)),
+            mode='constant')
+        edge = (cv2.dilate(edge, kernel, iterations=1) > 50) * 1.0
+
+        data['gt_fields'].append('edge')
+        data['edge'] = edge


这个比mask_to_binary_edge快，因为是没有使用到onehot的步骤。
但是这样获得的edge是每个类别的edge么，因为lable是0-18？

mask_to_binary_edge先生成onehot，再从onehot生成edge，但是最后又把全部类别的edge和在一起了，那似乎生成onehot就没有必要了。

paddleseg/models/losses/cross_entropy_loss.py

flytocc · 2023-11-01T09:05:12Z

模型权重有点问题，你重新给我提交下吧，我把链接给你～

什么问题

shiyutang · 2023-11-01T11:14:39Z

模型权重有点问题，你重新给我提交下吧，我把链接给你～

什么问题

没事，我先验证下。

flytocc · 2023-11-01T16:01:38Z

我使用2张V100进行了一次训练，mIoU为78.34%，官方权重的mIoU为78.74%，误差大约0.4%

当前的实现和官方有如下区别：

label不同：PaddleSeg使用*_labelTrainIds.png，PIDNet使用*_labelIds.png，二者有细微区别
数据增强padding_value不同： PaddleSeg填充127.5，PIDNet填充0
数据增强img resize不同： PaddleSeg中img为float32，PIDNet中img为uint8。这个差异较小，应该不影响训练
BatchNorm不同：PaddleSeg使用SyncBatchNorm，PIDNet使用的是普通的BatchNorm2d

另外，我也尝试了使用RandomDistort增强，基本没有提升(78.35)。

如果，你要进行训练，可以把padding_value设置为0：

train_dataset:
  transforms:
    - type: AddEdgeLabel
    - type: ResizeStepScaling
      min_scale_factor: 0.5
      max_scale_factor: 2.1
      scale_step_size: 0.1
    - type: RandomPaddingCrop
      crop_size: [1024, 1024]
      im_padding_value: 0   # <---------- here
    - type: RandomHorizontalFlip
    - type: Normalize
      mean: *mean
      std: *std

shiyutang · 2023-11-02T02:52:33Z

好，我在paddle=0上训练下。你那边能否看看标签的影响呢？另外我看标签不应该是影响，labelID是完整的33类数据，但是PID源码是19类的模型，辛苦看看如果没有转换，那模型和数据的类别是怎么匹配上的，如果可以匹配也可以用labelID训练下，探究下这方面的影响。https://www.cnblogs.com/dotman/p/cityscapes_dataset_tips.html

shiyutang · 2023-11-02T04:02:07Z

模型链接如下，另外你可以发下你的训练日志给我么？

https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_small_2xb6-120k_1024x1024-cityscapes.pdparams
https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_small_imagenet1k.pdparams
https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_medium_2xb6-120k_1024x1024-cityscapes.pdparams
https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_medium_imagenet1k.pdparams
https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_large_2xb6-120k_1024x1024-cityscapes.pdparams
https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_large_imagenet1k.pdparams

flytocc · 2023-11-02T07:42:37Z

好，我在paddle=0上训练下。你那边能否看看标签的影响呢？另外我看标签不应该是影响，labelID是完整的33类数据，但是PID源码是19类的模型，辛苦看看如果没有转换，那模型和数据的类别是怎么匹配上的

需要把33类的*_labelIds.png转换成19类。

https://github.com/mcordts/cityscapesScripts/blob/a7ac7b4062d1a80ed5e22d2ea2179c886801c77d/cityscapesscripts/helpers/labels.py#L62-L99

参考PIDNet的实现：

def convert_label(label: np.ndarray, ignore_label: int = 255) -> np.ndarray:
    label_mapping = {-1: ignore_label, 0: ignore_label, 
                     1: ignore_label, 2: ignore_label, 
                     3: ignore_label, 4: ignore_label, 
                     5: ignore_label, 6: ignore_label, 
                     7: 0, 8: 1, 9: ignore_label, 
                     10: ignore_label, 11: 2, 12: 3, 
                     13: 4, 14: ignore_label, 15: ignore_label, 
                     16: ignore_label, 17: 5, 18: ignore_label, 
                     19: 6, 20: 7, 21: 8, 22: 9, 23: 10, 24: 11,
                     25: 12, 26: 13, 27: 14, 28: 15, 
                     29: ignore_label, 30: ignore_label, 
                     31: 16, 32: 17, 33: 18}

    temp = label.copy()
    for v, k in label_mapping.items():
        temp[label == k] = v
    return temp

*_labelIds.png是数据集自带的，我不太清楚它具体是怎样生成的，换成成19类后，和*_labelTrainIds.png有细微的差别。

如果可以匹配也可以用labelID训练下，探究下这方面的影响。https://www.cnblogs.com/dotman/p/cityscapes_dataset_tips.html

我正在用转换后的*_labelIds.png进行训练。

flytocc · 2023-11-02T07:47:20Z

模型链接如下，另外你可以发下你的训练日志给我么？

https://pan.baidu.com/s/15HZ46FAJCNes8sxUDj36lQ?pwd=gvg9

shiyutang · 2023-11-03T02:44:11Z

替换padding=0后训练，精度还是有些差距。我修改padding重新训练一下。

flytocc · 2023-11-03T06:05:49Z

替换padding=0后训练，精度还是有些差距。我在padding ！=0重新训练一下。

77.74%确实有点低啊，padding=127.5我一共跑了三次，分别是78.32,78.34,78.35。

shiyutang · 2023-11-06T06:14:25Z

使用pad=默认值重新训练了一下，精度差距缩小。

shiyutang

精度结果基本满足预期，完成下列修改可合入：

对small模型的模型参数和日志都加上吧（
vdl：https://paddlepaddle.org.cn/paddle/visualdl/service/app?id=57dda9c34cd06a4b2996118df03583c9
model：https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_small_cityscapes_1024x1024_120k/model.pdparams
log：https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_small_cityscapes_1024x1024_120k/pidnet_small.log
），可行的话也加上medium和large的。
同时加一下tipc：https://github.com/PaddlePaddle/PaddleSeg/blob/release/2.8/test_tipc/docs/test_train_inference_python.md#22-%E5%8A%9F%E8%83%BD%E6%B5%8B%E8%AF%95 lite_tran_lite_infer模式即可，用于加入CI测试。

configs/pidnet/README.md

configs/pidnet/pidnet_large_cityscapes_1024x1024_120k.yml

paddleseg/models/losses/ohem_cross_entropy_loss.py

flytocc · 2023-11-06T09:50:21Z

tipc有点问题

在paddle2.5.1版本下，export.py会报错：

Traceback (most recent call last):
  File "/home/flytocc/workspaces/PaddleSeg/tools/export.py", line 121, in <module>
    main(args)
  File "/home/flytocc/workspaces/PaddleSeg/tools/export.py", line 89, in main
    paddle.jit.save(model, os.path.join(args.save_dir, save_name))
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/decorator.py", line 232, in fun
    return caller(func, *(extras + args), **kw)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/fluid/wrapped_decorator.py", line 25, in __impl__
    return wrapped_func(*args, **kwargs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/api.py", line 752, in wrapper
    func(layer, path, input_spec, **configs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/decorator.py", line 232, in fun
    return caller(func, *(extras + args), **kw)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/fluid/wrapped_decorator.py", line 25, in __impl__
    return wrapped_func(*args, **kwargs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/fluid/dygraph/base.py", line 75, in __impl__
    return func(*args, **kwargs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/api.py", line 1043, in save
    static_func.concrete_program_specify_input_spec(
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/program_translator.py", line 709, in concrete_program_specify_input_spec
    concrete_program, _ = self.get_concrete_program(
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/program_translator.py", line 589, in get_concrete_program
    concrete_program, partial_program_layer = self._program_cache[
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/program_translator.py", line 1249, in __getitem__
    self._caches[item_id] = self._build_once(item)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/program_translator.py", line 1193, in _build_once
    concrete_program = ConcreteProgram.from_func_spec(
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/decorator.py", line 232, in fun
    return caller(func, *(extras + args), **kw)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/fluid/wrapped_decorator.py", line 25, in __impl__
    return wrapped_func(*args, **kwargs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/fluid/dygraph/base.py", line 75, in __impl__
    return func(*args, **kwargs)
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/program_translator.py", line 1070, in from_func_spec
    error_data.raise_new_exception()
  File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/error.py", line 452, in raise_new_exception
    raise new_exception from None
ValueError: In transformed code:

    File "/home/flytocc/workspaces/PaddleSeg/paddleseg/deploy/export.py", line 26, in forward
        outs = self.model(x)
    File "/home/flytocc/workspaces/PaddleSeg/paddleseg/models/pidnet.py", line 69, in forward
        feat = self.backbone(x)
    File "/home/flytocc/workspaces/PaddleSeg/paddleseg/models/backbones/pidnet.py", line 681, in forward
        # stage 0-2
        x = self.stem(x)
        ~~~~~~~~~~~~~~~~ <--- HERE

        # stage 3

    File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/convert_call_func.py", line 222, in convert_call
        if is_builtin(func) or is_unsupported(func):
    File "/home/flytocc/anaconda3/envs/pd25/lib/python3.10/site-packages/paddle/jit/dy2static/convert_call_func.py", line 122, in is_unsupported
        func_in_dict = func == v

    ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (6,) + inhomogeneous part.

在paddle2.5.2版本下，export.py没报错，但infer.py会报错：

Traceback (most recent call last):
  File "<string>", line 1, in <module>
  File "/usr/lib/python3.8/multiprocessing/spawn.py", line 116, in spawn_main
    exitcode = _main(fd, parent_sentinel)
  File "/usr/lib/python3.8/multiprocessing/spawn.py", line 126, in _main
    self = reduction.pickle.load(from_parent)
  File "/usr/lib/python3.8/multiprocessing/synchronize.py", line 110, in __setstate__
    self._semlock = _multiprocessing.SemLock._rebuild(*state)
FileNotFoundError: [Errno 2] No such file or directory
Traceback (most recent call last):
  File "deploy/python/infer.py", line 396, in <module>
    main(args)
  File "deploy/python/infer.py", line 384, in main
    predictor.run(imgs_list)
  File "deploy/python/infer.py", line 219, in run
    self.predictor.run()
ValueError: (InvalidArgument) Broadcast dimension mismatch. Operands could not be broadcast together with the shape of X = [1, 32, 128, 256] and the shape of Y = [1, 32, 128, 128]. Received [256] in X is not equal to [128] in Y at i:3.
  [Hint: Expected x_dims_array[i] == y_dims_array[i] || x_dims_array[i] <= 1 || y_dims_array[i] <= 1 == true, but received x_dims_array[i] == y_dims_array[i] || x_dims_array[i] <= 1 || y_dims_array[i] <= 1:0 != true:1.] (at ../paddle/phi/kernels/funcs/common_shape.h:86)
  [operator < elementwise_mul > error]

flytocc · 2023-11-06T10:10:46Z

如果可以匹配也可以用labelID训练下，探究下这方面的影响。

我训练完成了，mIoU 78.40%，比labelTrainIds高0.05%，基本没什么影响

shiyutang

导出和推理在paddle develop上重新尝试下？看上去是形状不匹配，应该是动转静过程中的问题。

另外readme需要补充下。

shiyutang · 2023-11-07T02:09:33Z

configs/pidnet/README.md

+|PIDNet|PIDNet_Medium|1024x1024|120000|80.22%|82.05%|[model](https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_medium_2xb6-120k_1024x1024-cityscapes.pdparams)|
+|PIDNet|PIDNet-Large |1024x1024|120000|80.89%|82.37%|[model](https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_large_2xb6-120k_1024x1024-cityscapes.pdparams)|


这两个都是转换的模型而非训练模型，最好做一下区分。

m和l的模型都没训练，我先空着？

嗯嗯，可以训练下加入。

configs/pidnet/README.md

configs/pidnet/pidnet_small_cityscapes_1024x1024_120k.yml

shiyutang · 2023-11-07T02:18:26Z

paddle2.5.1版本下，export.py没报错

这两个都是2.5.1？

flytocc · 2023-11-07T06:52:13Z

paddle2.5.1版本下，export.py没报错

这两个都是2.5.1？

写错了，2.5.1版本下export.py报错，2.5.2版本下infer.py报错，稍后我试试develop

shiyutang

LGTM

pobi123 · 2024-04-25T17:57:19Z

我在使用paddleseg训练的时候，选用的是pp_liteseg_stdc1_camvid_960x720_10k。训练发生报错：
ValueError: (InvalidArgument) Broadcast dimension mismatch.
Operands could not be broadcast together with the shape of X = [20, 4147200] and the shape of Y = [12441600].
Received [4147200] in X is not equal to [12441600] in Y at i:1.
请问是什么原因？

flytocc · 2024-04-26T05:20:21Z

@pobi123 这是PIDNet的pr，pp_liteseg有什么问题建议直接提issue

我在使用paddleseg训练的时候，选用的是pp_liteseg_stdc1_camvid_960x720_10k。训练发生报错： ValueError: (InvalidArgument) Broadcast dimension mismatch. Operands could not be broadcast together with the shape of X = [20, 4147200] and the shape of Y = [12441600]. Received [4147200] in X is not equal to [12441600] in Y at i:1. 请问是什么原因？

Yana990 · 2024-06-16T06:59:43Z

500/500 [==============================] - 54s 107ms/step - batch_cost: 0.1071 - reader cost: 0.0861
Traceback (most recent call last):
File "train.py", line 230, in <module>
main(args)
File "train.py", line 206, in main
train(
File "/home/PaddleSeg-release-2.5/paddleseg/core/train.py", line 285, in train
mean_iou, acc, _, _, _ = evaluate(
File "/home/PaddleSeg-release-2.5/paddleseg/core/val.py", line 223, in evaluate
acc, class_precision, class_recall = metrics.class_measurement(
File "/home/PaddleSeg-release-2.5/paddleseg/utils/metrics.py", line 226, in class_measurement
return mean_acc, np.array(class_precision), np.array(class_recall)
ValueError: setting an array element with a sequence. The requested array has an inhomogeneous shape after 1 dimensions. The detected shape was (19,) + inhomogeneous part.

请问以上的报错怎么解决呢？

Add PIDNet

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paddle-bot bot added the contributor Contribution from developers label Oct 29, 2023

luotao1 mentioned this pull request Oct 30, 2023

【PaddlePaddle Hackathon 5th】开源贡献个人挑战赛 PaddlePaddle/Paddle#57262

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flytocc added 7 commits October 30, 2023 19:43

clean AddEdgeLabel

2a8aa9f

assert the length of weight

5d03c3b

remove used data aug

7a9487a

Not importing BasicBlock and Bottleneck from other modules

b2da245

update pidnet_small/medium/large configs

0874ea5

add README

45b8d2d

fix codestyle

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flytocc added 2 commits October 31, 2023 19:06

small fix

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fix RandomPaddingCrop

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update pretrained weights URL and train log

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[Feature]: Add PIDNet #3491

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【Hackathon 5th No.68】轻量语义分割网络PIDNet #3548

【Hackathon 5th No.68】轻量语义分割网络PIDNet #3548

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Yana990 commented Jun 16, 2024

		\|PIDNet\|PIDNet_Medium\|1024x1024\|120000\|80.22%\|82.05%\|[model](https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_medium_2xb6-120k_1024x1024-cityscapes.pdparams)\|
		\|PIDNet\|PIDNet-Large \|1024x1024\|120000\|80.89%\|82.37%\|[model](https://paddleseg.bj.bcebos.com/dygraph/pidnet/pidnet_large_2xb6-120k_1024x1024-cityscapes.pdparams)\|

【Hackathon 5th No.68】轻量语义分割网络PIDNet #3548

【Hackathon 5th No.68】轻量语义分割网络PIDNet #3548

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flytocc commented Oct 29, 2023 • edited Loading

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used AI Studio for training. Thanks a lot!

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