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HRSC2016 数据集 L2 L3 task
作者：繁依Fanyi0 | 2024-06-06 02:45:53
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hrsc2016
网上没有HRSC2016 数据集 L2 L3 task 任务的开源项目，我的毕设跟老师吹的牛是把数据集用到L2、L3任务上，现在发现没有开源代码，心态没了。
接下来这段时间尝试手写代码，完成这个任务。
0. GPU
还是接着之前使用的autodl 的GPU，当时保存镜像了，现在拖过来可以直接使用。
1.修改网络模型中 num_class=33
configs\obb\oriented_rcnn\faster_rcnn_orpn_r50_fpn_3x_hrsc.py
num_classes=1,改成33
2.修改 hrsc.py中 classwise=True
configs\obb_base_\datasets\hrsc.py
classwise=False,改成True
3.疑惑
训练读取的标签从哪读取？
为什么都没改读取标签的位置就能行？
因为数据集里的annotation还是labelTxt，用的是哪个我不确定。先把testdataset里边的labelTxt文件夹删掉进行测试。能运行，表示Oriented R-CNN没用labelTxt里边的文件，那我直接修改上边两处试试。
(obbdetection) root@container-bd721182ac-1b86a0fe:~/OBBDetection# python tools/test.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py /root/OBBDetection/work_dirs/epoch_35.pth --eval mAP Starting loading HRSC dataset information. 100%|███████████████████████████████████████████████████████████████████████████████████████| 444/444 [00:00<00:00, 4659.11it/s] Finishing loading HRSC, get 444 images, using 0.214s. load checkpoint from local path: /root/OBBDetection/work_dirs/epoch_35.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 9.9 task/s, elapsed: 45s, ETA: 0s +-------+------+------+--------+--------+ | class | gts | dets | recall | ap | +-------+------+------+--------+--------+ | ship | 1188 | 3160 | 0.9840 | 0.9049 | +-------+------+------+--------+--------+ | mAP | | | | 0.9049 | +-------+------+------+--------+--------+
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不确定： 现在看他的Annotation里的东西我们没用到。当时转化成txt格式了，后边都是ship，0/1，看来还得再转换一边。
4. 修改前 完整性测试
先运行一下 Train.py，确保修改之前正确。
nohup python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py --work-dir work_dirs >xcbTrain202205171509.log 2>&1 &
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可以正常训练。
5.然后修改参数
configs\obb\oriented_rcnn\faster_rcnn_orpn_r50_fpn_3x_hrsc.py
num_classes=1,改成33
configs\obb_base_\datasets\hrsc.py
classwise=False,改成True
nohup python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py --work-dir work_dirs >xcbTrain202205171520.log 2>&1 &
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2022年5月17日15点22分
训练一下，2080Ti的GPU 预计使用一个半小时。打游戏了。
可以看GPU的使用情况，2s刷新一次。
watch -n 2 -d nvidia-smi
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中途因为空间不够（他每次都生成xepoch.pth)，中断了，所以重新恢复训练。
这里注意，从Jupyter notebook 选中后右键删除的文件并没从磁盘上消失，也就是你的磁盘空间还是不足，因为他放入了回收站、c。
用这个代码清空回收站
rm -rf ~/.local/share/Trash/*
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可以用这个语句查询磁盘空间
df -h
或者
df /root/OBBDetection
其他等等。
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然后我们恢复训练。注意，我们上次失败是存储到epoch24.pth了。但是数据不全，所以从epoch23.pth开始恢复
nohup python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py --work-dir work_dirs --resume-from work_dirs/epoch_23.pth >xcbTrain202205171647.log 2>&1 &
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训练完成了，让我们找个图片测试。
6.测试图片
python demo/image_demo.py demo/100001132.bmp configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py work_dirs/epoch_36.pth
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贴上几张图片。
注意：每个预测框上的第一个数字表示33个类型，比如09表示佩里级护卫舰 perry class frigate。这个文件在imageset里叫 sysdata.xml
下面是sysdata.xml 部分标签的参考：
7. 评价 mAP
先用VOC07评价：
(obbdetection) root@container-bd721182ac-1b86a0fe:~/OBBDetection# python tools/test.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py /root/OBBDetection/work_dirs/epoch_36.pth --eval mAP --options use_07_metric=True Starting loading HRSC dataset information. 100%|█████████████████████████████████████████████████████████████████████████| 444/444 [00:00<00:00, 5789.69it/s] Finishing loading HRSC, get 444 images, using 0.148s. load checkpoint from local path: /root/OBBDetection/work_dirs/epoch_36.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.0 task/s, elapsed: 44s, ETA: 0s +-------+-----+------+--------+--------+ | class | gts | dets | recall | ap | +-------+-----+------+--------+--------+ | 01 | 230 | 547 | 0.8391 | 0.6287 | | 02 | 0 | 0 | 0.0000 | 0.0000 | | 03 | 22 | 284 | 0.9091 | 0.1458 | | 04 | 2 | 0 | 0.0000 | 0.0000 | | 05 | 35 | 70 | 1.0000 | 0.8107 | | 06 | 12 | 76 | 0.9167 | 0.4671 | | 07 | 158 | 293 | 0.9684 | 0.8945 | | 08 | 40 | 111 | 0.9250 | 0.8055 | | 09 | 128 | 268 | 0.9766 | 0.8960 | | 10 | 22 | 103 | 1.0000 | 0.9716 | | 11 | 103 | 212 | 0.9806 | 0.9072 | | 12 | 1 | 0 | 0.0000 | 0.0000 | | 13 | 2 | 68 | 1.0000 | 0.4000 | | 14 | 0 | 0 | 0.0000 | 0.0000 | | 15 | 35 | 93 | 1.0000 | 0.9225 | | 16 | 50 | 84 | 1.0000 | 0.9917 | | 17 | 1 | 0 | 0.0000 | 0.0000 | | 18 | 18 | 49 | 0.8889 | 0.6243 | | 19 | 39 | 112 | 0.9487 | 0.8279 | | 20 | 16 | 32 | 1.0000 | 0.9192 | | 21 | 0 | 0 | 0.0000 | 0.0000 | | 22 | 50 | 73 | 0.9200 | 0.7254 | | 23 | 0 | 0 | 0.0000 | 0.0000 | | 24 | 1 | 34 | 1.0000 | 0.0303 | | 25 | 119 | 214 | 0.9076 | 0.8259 | | 26 | 4 | 69 | 1.0000 | 0.4387 | | 27 | 60 | 82 | 0.9500 | 0.8959 | | 28 | 4 | 7 | 0.7500 | 0.4870 | | 29 | 10 | 79 | 1.0000 | 0.9587 | | 30 | 16 | 57 | 0.9375 | 0.8745 | | 31 | 0 | 0 | 0.0000 | 0.0000 | | 32 | 10 | 67 | 1.0000 | 0.9504 | | 33 | 0 | 0 | 0.0000 | 0.0000 | +-------+-----+------+--------+--------+ | mAP | | | | 0.6444 | +-------+-----+------+--------+--------+
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用VOC12评价
python tools/test.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py /root/OBBDetection/work_dirs/epoch_36.pth --eval mAP --options use_07_metric=False Starting loading HRSC dataset information. 100%|█████████████████████████████████████████████████████████████████████████| 444/444 [00:00<00:00, 6964.86it/s] Finishing loading HRSC, get 444 images, using 0.139s. load checkpoint from local path: /root/OBBDetection/work_dirs/epoch_36.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.0 task/s, elapsed: 44s, ETA: 0s +-------+-----+------+--------+--------+ | class | gts | dets | recall | ap | +-------+-----+------+--------+--------+ | 01 | 230 | 547 | 0.8391 | 0.6419 | | 02 | 0 | 0 | 0.0000 | 0.0000 | | 03 | 22 | 284 | 0.9091 | 0.1445 | | 04 | 2 | 0 | 0.0000 | 0.0000 | | 05 | 35 | 70 | 1.0000 | 0.8120 | | 06 | 12 | 76 | 0.9167 | 0.4504 | | 07 | 158 | 293 | 0.9684 | 0.9453 | | 08 | 40 | 111 | 0.9250 | 0.8261 | | 09 | 128 | 268 | 0.9766 | 0.9495 | | 10 | 22 | 103 | 1.0000 | 0.9755 | | 11 | 103 | 212 | 0.9806 | 0.9726 | | 12 | 1 | 0 | 0.0000 | 0.0000 | | 13 | 2 | 68 | 1.0000 | 0.4000 | | 14 | 0 | 0 | 0.0000 | 0.0000 | | 15 | 35 | 93 | 1.0000 | 0.9441 | | 16 | 50 | 84 | 1.0000 | 0.9970 | | 17 | 1 | 0 | 0.0000 | 0.0000 | | 18 | 18 | 49 | 0.8889 | 0.6429 | | 19 | 39 | 112 | 0.9487 | 0.8628 | | 20 | 16 | 32 | 1.0000 | 0.9236 | | 21 | 0 | 0 | 0.0000 | 0.0000 | | 22 | 50 | 73 | 0.9200 | 0.7296 | | 23 | 0 | 0 | 0.0000 | 0.0000 | | 24 | 1 | 34 | 1.0000 | 0.0303 | | 25 | 119 | 214 | 0.9076 | 0.8414 | | 26 | 4 | 69 | 1.0000 | 0.4248 | | 27 | 60 | 82 | 0.9500 | 0.9305 | | 28 | 4 | 7 | 0.7500 | 0.4821 | | 29 | 10 | 79 | 1.0000 | 0.9636 | | 30 | 16 | 57 | 0.9375 | 0.9014 | | 31 | 0 | 0 | 0.0000 | 0.0000 | | 32 | 10 | 67 | 1.0000 | 0.9455 | | 33 | 0 | 0 | 0.0000 | 0.0000 | +-------+-----+------+--------+--------+ | mAP | | | | 0.6569 | +-------+-----+------+--------+--------+
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我找到了有两篇做了L3\L2 task的文章他们没开源
分别是：
Ship detection and classification from optical
remote sensing images: A survey
好像是民航和北航联合做的，删掉了不存在的类
还有一篇西电的硕士毕业论文：
基于深度学习的卫星图像目标检测算法研究_李巍
精度我也没看他们用的VOC几，因为目前类的数量不同。
本文参考的代码上直接使用了33类的，就是HRSC2016自带的所有标签，可以看出有些标签根本不存在，可能他们的文章为了美观没放上去，这个后续再说吧。
我下一步尝试进行L2 级别的task。
L2 task
说来很惭愧，我自己什么都没做，只是改了几处代码 :<
现在已知的信息是：
1.能做L1 task 分类，只有ship 1 class
2.能做L3 task 分类，有 33 classs
修改的地方只有 classwise 和 num_class
接下来把num_class 改成四试试。
然后在BboxToolkit\datasets\misc.py文件中加入
'HRSC_4cls': ('01', '02', '03', '04'),
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还得在dataset_aliases
加入
'HRSC_cls': product(['hrsc', 'HRSC'], ['_4cls', '2016_4cls']),
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在mmdet\datasets\obb\hrsc.py中
修改：
if classwise:
HRSCDataset.CLASSES = bt.get_classes('hrsc_4cls')
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然后进行测试。
忙着头做的，也不知道行不行，好紧张。一个小时后见分晓。
2022年5月17日19点25分
打游戏去。
nohup python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py --work-dir work_dirs >xcbTrain202205171920.log 2>&1 &
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8.完了
‘HRSC_4cls’: product([‘hrsc’, ‘HRSC’], [‘_4cls’, ‘2016_4cls’]),
这个地方训练之前HRSC_CLS
忘记加4了，先试试epoch5.pth 怎么样。
epoch5,7,10 都检测不出来，
log显示 坏了
刚才粗心了，现在重新训练。
9.失败了
(obbdetection) root@container-bd721182ac-1b86a0fe:~/OBBDetection# python tools/test.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py /root/OBBDetection/work_dirs/epoch_36.pth --eval mAP Starting loading HRSC dataset information. 100%|████████████████████████████████████████████████████████████████████████| 444/444 [00:00<00:00, 10876.42it/s] Finishing loading HRSC, get 444 images, using 0.131s. load checkpoint from local path: /root/OBBDetection/work_dirs/epoch_36.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.2 task/s, elapsed: 44s, ETA: 0s +-------+-----+------+--------+--------+ | class | gts | dets | recall | ap | +-------+-----+------+--------+--------+ | 01 | 230 | 1668 | 0.7913 | 0.5600 | | 02 | 0 | 1158 | 0.0000 | 0.0000 | | 03 | 22 | 1516 | 0.5000 | 0.1264 | | 04 | 2 | 1147 | 0.0000 | 0.0000 | +-------+-----+------+--------+--------+ | mAP | | | | 0.2288 | +-------+-----+------+--------+--------+
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肯定是读取的标签不对，相当于我把33个类减到四个类了c。
肯定得从读取标签的地方入手。
9.load annotation 修改
BboxToolkit\datasets\HRSCio.py文件中，
修改Class_ID为HRS_Class_ID
cls = obj.find('Class_ID').text
改为
cls = obj.find('HRS_Class_ID').text
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报错了，这个是sysdata.xml的名称，应该改每张图片对应的annotation的
应该把他加载annotation的代码，Class_ID为HRS_Class_ID。明天再说，今天腰疼了。
2022年5月19日16点33分
把注释掉的改为这几个判断。然后训练试试。
if cls2lbl[cls] in [1,2,3,4,27]:
labels.append(1)
if cls2lbl[cls] in [5,6,12,13,16,31,32,33]:
labels.append(2)
if cls2lbl[cls] in [7,8,9,10,11,14,15,17,19,28,29]:
labels.append(3)
if cls2lbl[cls] in [18,20,22,24,25,26,30]:
labels.append(4)
# labels.append(cls2lbl[cls])
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先保持 num_class = 33
训练12epoch试试结果。
改的乱七八糟，很多运行错误。重新清除一下，刷新一下镜像。
再次说明了跑程序之前验证一下完整性的重要。
重新恢复
33 类正常运行
nohup python tools/train.py configs/obb/oriented_rcnn/faster_rcnn_orpn_r101_fpn_3x_hrsc.py --work-dir work_dirs >xxxcbtrain202204051625.log 2>&1 &
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只修改HRSCio.py 里边
if cls2lbl[cls] in [1,2,3,4,27]:
labels.append(1)
if cls2lbl[cls] in [5,6,12,13,16,31,32,33]:
labels.append(2)
if cls2lbl[cls] in [7,8,9,10,11,14,15,17,19,28,29]:
labels.append(3)
if cls2lbl[cls] in [18,20,22,24,25,26,30]:
labels.append(4)
报错：
IndexError: index 0 is out of bounds for dimension 0 with size 0
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大概是有些范围超了。
然后修改了
BboxToolkit\datasets\misc.py
中：
'HRSC_4cls': ('01', '02', '03', '04'),
'HRSC_4cls': product(['hrsc', 'HRSC'], ['_4cls', '2016_4cls']),
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修改：
mmdet\datasets\obb\hrsc.py
中
HRSCDataset.CLASSES = bt.get_classes('hrsc_4cls')
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运行试试
还是越界。
把config的num_class 改成4，还是越界。
吃饭了 17点22分
晚上奋战30mins
捋着错误找找，进一步有进一步的欢喜。
2022-05-19 21:12:32,653 - mmdet - INFO - Epoch [1][50/219] lr: 4.945e-04, eta: 0:57:05, time: 0.437, data_time: 0.055, memory: 5327, loss_rpn_cls: 0.4885, loss_rpn_bbox: 0.0252, loss_cls: 0.3598, acc: 88.0039, loss_bbox: 0.0000, loss: 0.8735, grad_norm: 8.2542 谢昌贝 assigned_labels.shape= torch.Size([2000]) assigned_gt_inds= tensor([0, 0, 0, ..., 0, 0, 0], device='cuda:0') gt_labels= tensor([], device='cuda:0', dtype=torch.int64) Traceback (most recent call last): File "tools/train.py", line 153, in <module> main() File "tools/train.py", line 149, in main meta=meta) File "/root/OBBDetection/mmdet/apis/train.py", line 133, in train_detector runner.run(data_loaders, cfg.workflow, cfg.total_epochs) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 127, in run epoch_runner(data_loaders[i], **kwargs) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 50, in train self.run_iter(data_batch, train_mode=True, **kwargs) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/runner/epoch_based_runner.py", line 30, in run_iter **kwargs) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/mmcv/parallel/data_parallel.py", line 75, in train_step return self.module.train_step(*inputs[0], **kwargs[0]) File "/root/OBBDetection/mmdet/models/detectors/base.py", line 237, in train_step losses = self(**data) File "/root/miniconda3/envs/obbdetection/lib/python3.7/site-packages/torch/nn/modules/module.py", line 722, in _call_impl result = self.forward(*input, **kwargs) File "/root/OBBDetection/mmdet/core/fp16/decorators.py", line 51, in new_func return old_func(*args, **kwargs) File "/root/OBBDetection/mmdet/models/detectors/base.py", line 172, in forward return self.forward_train(img, img_metas, **kwargs) File "/root/OBBDetection/mmdet/models/detectors/obb/obb_two_stage.py", line 181, in forward_train **kwargs) File "/root/OBBDetection/mmdet/models/roi_heads/obb/obb_standard_roi_head.py", line 117, in forward_train target_bboxes_ignore[i], gt_labels[i]) File "/root/OBBDetection/mmdet/core/bbox/assigners/max_iou_assigner.py", line 119, in assign assign_result = self.assign_wrt_overlaps(overlaps, gt_labels) File "/root/OBBDetection/mmdet/core/bbox/assigners/max_iou_assigner.py", line 211, in assign_wrt_overlaps assigned_gt_inds[pos_inds] - 1] IndexError: index is out of bounds for dimension with size 0
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最后一行倒着看，数组越界了，从下往上看了一遍代码，中间那几个地方没看，我估计是gt_labels没得到值，所以才出问题的。
可能是修改了几个标签后，反向传播的时候丢了，或者没搞进去。
现在gt_labels是空的
查看了很多遍之后，发现判断加1、2、3、4可能会出现空的情况
if cls2lbl[cls]+1 in [1,2,3,4,27]:
print("labels.append(1)")
labels.append(1)
if cls2lbl[cls]+1 in [5,6,12,13,16,31,32,33]:
print("labels.append(1)")
labels.append(2)
if cls2lbl[cls]+1 in [7,8,9,10,11,14,15,17,19,28,29]:
print("labels.append(1)")
labels.append(3)
if cls2lbl[cls]+1 in [18,20,22,24,25,26,30]:
print("labels.append(1)")
labels.append(4)
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刚才输入的标签是1~4，可能识别的有问题：评价精度如下：
labels = valid_mask.nonzero()[:, 1]
[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.2 task/s, elapsed: 44s, ETA: 0s
+-------+-----+------+--------+--------+
| class | gts | dets | recall | ap |
+-------+-----+------+--------+--------+
| 01 | 0 | 1502 | 0.0000 | 0.0000 |
| 02 | 254 | 2744 | 0.7480 | 0.3475 |
| 03 | 0 | 1514 | 0.0000 | 0.0000 |
| 04 | 0 | 1508 | 0.0000 | 0.0000 |
+-------+-----+------+--------+--------+
| mAP | | | | 0.3475 |
+-------+-----+------+--------+--------+
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精度很低，现在改到了0~3，，尝试resume-from试试，因为从头训练成本高啊（也不知道行不行，）
2022年5月19日22点25分，还有半小时熄灯了。快点快点
可能跟开始的位置也有关系吧。
从epoch17 resume 到 22epoch。
[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.7 task/s, elapsed: 42s, ETA: 0s
+-------+-----+------+--------+--------+
| class | gts | dets | recall | ap |
+-------+-----+------+--------+--------+
| 01 | 254 | 3017 | 0.7520 | 0.4733 |
| 02 | 0 | 2023 | 0.0000 | 0.0000 |
| 03 | 0 | 2003 | 0.0000 | 0.0000 |
| 04 | 0 | 2009 | 0.0000 | 0.0000 |
+-------+-----+------+--------+--------+
| mAP | | | | 0.4733 |
+-------+-----+------+--------+--------+
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明天接着搞。
找到一处没返回成4cls的字符串。
这次再试试。
mmdet/datasets/obb/hrsc.py
line52
def pre_pipeline(self, results):
results[‘4cls’] = self.CLASSES
还是不行，可能有的地方缺少乐。
直接把标签改成(1,2,3,4)
修改的地方如下：
booktool/dataset/hrsc.py中改 'HRSC_cls': product(['hrsc', 'HRSC'], ['_4cls', '2016_4cls']), 'HRSC_cls': ('01', '02', '03', '04'), config/obb/orcnn/fasxxx.py中改 num_classes=4, HRSCio.py中改 if cls2lbl[cls]+1 in [1,2,3,4,27]: print("labels.append(1)") labels.append(0) if cls2lbl[cls]+1 in [5,6,12,13,16,31,32,33]: print("labels.append(1)") labels.append(1) if cls2lbl[cls]+1 in [7,8,9,10,11,14,15,17,19,28,29]: print("labels.append(1)") labels.append(2) if cls2lbl[cls]+1 in [18,20,22,24,25,26,30]: print("labels.append(1)") labels.append(3) # labels.append(cls2lbl[cls])
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终于能显示正常的4个了，泪目，
2022年5月20日11点13分
人家都在过情人节，俺也干饭去了。
load checkpoint from local path: /root/autodl-nas/epoch/epoch_3.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.2 task/s, elapsed: 43s, ETA: 0s +-------+-----+------+--------+--------+ | class | gts | dets | recall | ap | +-------+-----+------+--------+--------+ | 01 | 314 | 3604 | 0.2866 | 0.0499 | | 02 | 110 | 3078 | 0.4000 | 0.1148 | | 03 | 540 | 3489 | 0.5167 | 0.3083 | | 04 | 224 | 3941 | 0.5089 | 0.0767 | +-------+-----+------+--------+--------+ | mAP | | | | 0.1374 | +-------+-----+------+--------+--------+
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load checkpoint from local path: /root/autodl-nas/epoch/epoch_9.pth [ ] 0/444, elapsed: 0s, ETA:/root/OBBDetection/mmdet/core/post_processing/obb/obb_nms.py:29: UserWarning: This overload of nonzero is deprecated: nonzero() Consider using one of the following signatures instead: nonzero(*, bool as_tuple) (Triggered internally at /opt/conda/conda-bld/pytorch_1595629403081/work/torch/csrc/utils/python_arg_parser.cpp:766.) labels = valid_mask.nonzero()[:, 1] [>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.1 task/s, elapsed: 44s, ETA: 0s +-------+-----+------+--------+--------+ | class | gts | dets | recall | ap | +-------+-----+------+--------+--------+ | 01 | 314 | 2376 | 0.8153 | 0.4269 | | 02 | 110 | 1018 | 0.7909 | 0.6111 | | 03 | 540 | 2078 | 0.9574 | 0.8249 | | 04 | 224 | 1618 | 0.8170 | 0.5311 | +-------+-----+------+--------+--------+ | mAP | | | | 0.5985 | +-------+-----+------+--------+--------+
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最后的结果
结果应该是可以的吧，感动死了
[>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>>] 444/444, 10.7 task/s, elapsed: 42s, ETA: 0s
+-------+-----+------+--------+--------+
| class | gts | dets | recall | ap |
+-------+-----+------+--------+--------+
| 01 | 314 | 5140 | 0.8917 | 0.6404 |
| 02 | 110 | 4529 | 1.0000 | 0.9828 |
| 03 | 540 | 5068 | 0.9907 | 0.8885 |
| 04 | 224 | 4765 | 0.9152 | 0.8066 |
+-------+-----+------+--------+--------+
| mAP | | | | 0.8296 |
+-------+-----+------+--------+--------+
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show img
睡觉 2022年5月20日14点37分
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