From dea3f31b1f671d37fa83a7d89ce5a599532ae8fc Mon Sep 17 00:00:00 2001 From: ximitiejiang Date: Wed, 4 Dec 2019 22:53:59 +0800 Subject: [PATCH] update --- demo/readme_base.md | 7 ++ ...ctor_retinanet_resnet50_voc.cpython-37.pyc | Bin 0 -> 2790 bytes .../cfg_detector_retinanet_resnet50_voc.py | 51 ++++----- .../test_detector_retinanet_voc.py | 61 ++++++++++ .../__pycache__/get_target_lib.cpython-37.pyc | Bin 7581 -> 7583 bytes model/__pycache__/loss_lib.cpython-37.pyc | Bin 5573 -> 5846 bytes .../__pycache__/retinanet_head.cpython-37.pyc | Bin 0 -> 5874 bytes .../__pycache__/ssd_head.cpython-37.pyc | Bin 12965 -> 13094 bytes model/bbox_head/retinanet_head.py | 106 ++++++++++-------- model/bbox_head/ssd_head.py | 14 ++- model/get_target_lib.py | 8 +- model/loss_lib.py | 17 ++- .../neck/__pycache__/neck_lib.cpython-37.pyc | Bin 7348 -> 7577 bytes model/neck/neck_lib.py | 8 +- .../prepare_training.cpython-37.pyc | Bin 15605 -> 15693 bytes utils/__pycache__/tools.cpython-37.pyc | Bin 13324 -> 14645 bytes utils/bbox_kmean.py | 6 +- utils/prepare_training.py | 2 + v01/model/__pycache__/losses.cpython-37.pyc | Bin 3467 -> 3479 bytes .../__pycache__/retina_head.cpython-37.pyc | Bin 8327 -> 8327 bytes v01/model/losses.py | 2 +- v01/model/retina_head.py | 10 +- .../__pycache__/anchor_target.cpython-37.pyc | Bin 16139 -> 16138 bytes v01/utils/anchor_target.py | 2 +- .../retinanet_voc/20191204_081458.log | 4 + .../retinanet_voc/20191204_100657.log | 2 + .../retinanet_voc/20191204_143156.log | 4 + .../retinanet_voc/20191204_143322.log | 2 + 28 files changed, 209 insertions(+), 97 deletions(-) create mode 100644 demo/retinanet_voc/__pycache__/cfg_detector_retinanet_resnet50_voc.cpython-37.pyc create mode 100644 demo/retinanet_voc/test_detector_retinanet_voc.py create mode 100644 model/bbox_head/__pycache__/retinanet_head.cpython-37.pyc create mode 100644 v01/work_dirs/retinanet_voc/20191204_081458.log create mode 100644 v01/work_dirs/retinanet_voc/20191204_100657.log create mode 100644 v01/work_dirs/retinanet_voc/20191204_143156.log create mode 100644 v01/work_dirs/retinanet_voc/20191204_143322.log diff --git a/demo/readme_base.md b/demo/readme_base.md index 51eeb54..ef6ccf3 100644 --- a/demo/readme_base.md +++ b/demo/readme_base.md @@ -509,6 +509,13 @@ 直到得到bbox正常的数据才return +### 训练中报错，binary_cross_entropy_with_logits(pred, target, weight)损失函数报错：RuntimeError: the derivative for 'weight' is not implemented + +1. 这个问题主要原因在于传入的weight是带有梯度反传标志的，但二值交叉熵公式并不支持对weight进行梯度反传更新。所以报错。 +实际上我并不需要weight进行梯度反传，之前的旧版本pytorch似乎不会报错，现在pytorch1.1爆出来反而是好事。 +解决方案：weight.detach()代替weight +参考：https://blog.csdn.net/sinat_24424445/article/details/101022092 + ### 训练中报错variable has been modified by an inplace operation： diff --git a/demo/retinanet_voc/__pycache__/cfg_detector_retinanet_resnet50_voc.cpython-37.pyc b/demo/retinanet_voc/__pycache__/cfg_detector_retinanet_resnet50_voc.cpython-37.pyc new file mode 100644 index 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workers_per_core if gpus>0 else imgs_per_core, + batch_size=imgs_per_core, + num_workers=workers_per_core, pin_memory=False, # 数据送入GPU进行加速(默认False) drop_last=False, collate_fn='dict_collate', # 'default_collate','multi_collate', 'dict_collate' @@ -145,14 +153,3 @@ momentum=0.9, weight_decay=5e-4)) -loss_clf = dict( - type='cross_entropy', - params=dict( - reduction='mean' - )) - -loss_reg = dict( - type='smooth_l1', - params=dict( - reduction='mean' - )) diff --git a/demo/retinanet_voc/test_detector_retinanet_voc.py b/demo/retinanet_voc/test_detector_retinanet_voc.py new file mode 100644 index 0000000..5646f52 --- /dev/null +++ b/demo/retinanet_voc/test_detector_retinanet_voc.py @@ -0,0 +1,61 @@ +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Created on Tue Sep 3 21:29:33 2019 + +@author: ubuntu +""" +import cv2 +from model.runner_lib import Runner +from utils.prepare_training import get_config +from utils.evaluation import eval_dataset_det, DetPredictor +from utils.tools import parse_log +from utils.dataset_classes import get_classes +from utils.visualization import vis_all_opencv, vis_all_pyplot, vis_cam + +def train_ssd(cfg_path, resume_from=None): + + runner = Runner(cfg, resume_from) + runner.train() + + + +if __name__ == "__main__": + + task = 'train' + cfg_path = './cfg_detector_retinanet_resnet50_voc.py' + cfg = get_config(cfg_path) + + if task == 'train': # 模型训练 + train_ssd(cfg, + resume_from=None) +# +# if task == 'log': +# parse_log(paths = ['/home/ubuntu/mytrain/ssd_vgg_voc/20191025_182352.log']) +# +# if task == 'eval': # 数据集评估 +# eval_dataset_det(cfg_path=cfg_path, +# load_from = '/home/ubuntu/mytrain/ssd_vgg_voc/epoch_11.pth', +# load_device='cuda') +# +# if task == 'load': # 已有数据集评估文件，重新载入进行评估 +# eval_dataset_det(cfg_path=cfg_path, +# load_from = '/home/ubuntu/mytrain/ssd_vgg_voc/epoch_11.pth', +# load_device='cuda', +# result_file='/home/ubuntu/mytrain/ssd_vgg_voc/20190928_084133_eval_result.pkl') +# +# if task == 'test': # 测试单张图或多张图的结果： cpu上0.649 sec， gpu上0.388 sec +# img = cv2.imread('/home/ubuntu/MyDatasets/misc/test13.jpg') +# predictor = DetPredictor(cfg_path, +# load_from = '/home/ubuntu/mytrain/ssd_vgg_voc/epoch_61.pth', +# load_device='cpu') +# for results in predictor([img]): +# vis_all_pyplot(*results, class_names=get_classes('voc'), score_thr=0.5) +# +# if task == 'video': # 测试视频预测结果：注意方法稍有不同，vis_cam需要传入一个predictor +# src = 0 # src可以等于int(cam_id), str(video path), list(img_list) +# predictor = DetPredictor(cfg_path, +# load_from = '/home/ubuntu/mytrain/ssd_vgg_voc/epoch_11.pth', +# load_device='cpu') +# vis_cam(src, predictor, class_names=get_classes('voc'), score_thr=0.2) +# \ No newline at end of file diff --git a/model/__pycache__/get_target_lib.cpython-37.pyc b/model/__pycache__/get_target_lib.cpython-37.pyc index 324cb84f389cffbf3d18d43969325e10f99c6cb4..b811cb3bd22d1411436e833b857157370fdc6002 100644 GIT binary patch delta 75 zcmbPhJ>QzwiIIU~L#u_!&YWb;DyOnzaZ Pg8a<95>yE}@kTZPTwNI2 diff --git 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init_weights(self): - common_init_weights(self) + """FPN初始化，mmdetection采用的是Xavier，但如果带了relu的话Xavier似乎不是最好选择，这里改成kaiming初始化""" + for m in self.modules(): + if isinstance(m, nn.Conv2d): + kaiming_init(m) +# common_init_weights(self) # %% diff --git a/utils/__pycache__/prepare_training.cpython-37.pyc b/utils/__pycache__/prepare_training.cpython-37.pyc index 3a2f3ff6d8433da2626c93c6fac186cf32ab1dfa..608657bdc31454777f502738d520772ad368a47c 100644 GIT binary patch delta 2759 zcmZuzYitzP72Z4h@OszY7+4u7#xG*K6TsMpUFIuE&{)~L3-owR$5wT4S;`OK)65H`=i5+4mUXRJ+V)&%-iUD5} z##qSQbMCxhBnGwTV5aZlo@3n<36PFM`b-Sun#v#FNe>JWmWS+=eF3xm~b*&d;f9 zcO2={eqTpF(|~UfRoE6Y)v1%5)Q>sNQN%jL1vFGTwmJWV4ox_jVPNMbS=Bd&$@{5LV=*q)y& zx}_Z}RI26ZUYasl5cQ_AC5grU4c?=26j-GkuHa0XVJQqWV#NIuG_HpcM!-`STKdPA zXwXEr7onLtmoU`^wX!gc{f}!3B6vVNcpF*aX9P29uyxJy-=b;O!7pg!mjv&qsn$*1 zzb3Ox@H>LaVk&E{94cYw{9EOUsw=IV+12uYT5p8!rM(Yoys7EQNk^K|O1J2)dykmj zCkPO*Hnp7RoUG?@zF0`0_`6k4$NysFg&Wt~xiLmf56>&n*|Sd*5LJ-GrExFomK;3( z5$skl! 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注意：二值交叉熵公式禁止传入的weight带有梯度反传标志，所以必须让weight先detach才行。 def weighted_sigmoid_focal_loss(pred, diff --git a/v01/model/retina_head.py b/v01/model/retina_head.py index 9f39e19..1a43b4e 100644 --- a/v01/model/retina_head.py +++ b/v01/model/retina_head.py @@ -149,15 +149,15 @@ def get_anchors(self, featmap_sizes, img_metas): def loss_single(self, cls_score, bbox_pred, labels, label_weights, bbox_targets, bbox_weights, num_total_samples, cfg): - # classification loss + """""" if self.use_sigmoid_cls: - labels = labels.reshape(-1, self.cls_out_channels) - label_weights = label_weights.reshape(-1, self.cls_out_channels) + labels = labels.reshape(-1, self.cls_out_channels) # (4, 151200, 20)->(604800, 20) + label_weights = label_weights.reshape(-1, self.cls_out_channels) # (4, 151200, 20)->(604800, 20) else: labels = labels.reshape(-1) label_weights = label_weights.reshape(-1) cls_score = cls_score.permute(0, 2, 3, 1).reshape( - -1, self.cls_out_channels) + -1, self.cls_out_channels) # (4, 9*20, h, w) -> (4*9*h*w, 20)=(604800, 20) if self.use_sigmoid_cls: if self.use_focal_loss: cls_criterion = weighted_sigmoid_focal_loss @@ -216,7 +216,7 @@ def loss(self, cls_scores, bbox_preds, gt_bboxes, gt_labels, img_metas, (labels_list, label_weights_list, bbox_targets_list, bbox_weights_list, num_total_pos, num_total_neg) = cls_reg_targets num_total_samples = (num_total_pos if self.use_focal_loss else - num_total_pos + num_total_neg) + num_total_pos + num_total_neg) # retinanet只取正样本 losses_cls, losses_reg = multi_apply( self.loss_single, cls_scores, diff --git a/v01/utils/__pycache__/anchor_target.cpython-37.pyc b/v01/utils/__pycache__/anchor_target.cpython-37.pyc index 50551927ebeac36ba5575bb3bdc8b7b4986ad2fc..e6315ad0ae39bbc2429dad53cc44849a0d5e6282 100644 GIT binary patch delta 2642 zcmZ`*U2IfE6lS`+x7+P*cgvQRwp6yIwA~g2T8fmP3Mi-n5oip-1g^Kcx3^cfdzZO) zDWFm?V*HEI3{f8pQjtG-FuD&$66L`JjDXRI4~#zvgan@yO!P?;=Q|gnG_uWpojG&n z%$#$+b7o)N^U9v8Rk2uPiu#HQRUm_|z1x)Gyg8~56>~XWPr{s& 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label_weights.view(-1, 1).expand( + bin_label_weights = label_weights.view(-1, 1).expand( # (201600)->(201600, 20)，相当于把第一列复制20份 label_weights.size(0), label_channels) return bin_labels, bin_label_weights diff --git a/v01/work_dirs/retinanet_voc/20191204_081458.log b/v01/work_dirs/retinanet_voc/20191204_081458.log new file mode 100644 index 0000000..f336075 --- /dev/null +++ b/v01/work_dirs/retinanet_voc/20191204_081458.log @@ -0,0 +1,4 @@ +2019-12-04 08:14:58,809 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 08:14:58,810 - INFO - workflow: [('train', 1)], max: 20 epochs +2019-12-04 10:06:57,961 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 10:06:57,961 - INFO - workflow: [('train', 1)], max: 20 epochs diff --git a/v01/work_dirs/retinanet_voc/20191204_100657.log b/v01/work_dirs/retinanet_voc/20191204_100657.log new file mode 100644 index 0000000..6b69ae1 --- /dev/null +++ b/v01/work_dirs/retinanet_voc/20191204_100657.log @@ -0,0 +1,2 @@ +2019-12-04 10:06:57,961 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 10:06:57,961 - INFO - workflow: [('train', 1)], max: 20 epochs diff --git a/v01/work_dirs/retinanet_voc/20191204_143156.log b/v01/work_dirs/retinanet_voc/20191204_143156.log new file mode 100644 index 0000000..9c05007 --- /dev/null +++ b/v01/work_dirs/retinanet_voc/20191204_143156.log @@ -0,0 +1,4 @@ +2019-12-04 14:31:56,745 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 14:31:56,746 - INFO - workflow: [('train', 1)], max: 20 epochs +2019-12-04 14:33:22,857 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 14:33:22,858 - INFO - workflow: [('train', 1)], max: 20 epochs diff --git a/v01/work_dirs/retinanet_voc/20191204_143322.log b/v01/work_dirs/retinanet_voc/20191204_143322.log new file mode 100644 index 0000000..da01405 --- /dev/null +++ b/v01/work_dirs/retinanet_voc/20191204_143322.log @@ -0,0 +1,2 @@ +2019-12-04 14:33:22,857 - INFO - Start running, host: ubuntu@ubun, work_dir: /home/ubuntu/suliang_git/deep_learning_algorithm/v01/work_dirs/retinanet_voc +2019-12-04 14:33:22,858 - INFO - workflow: [('train', 1)], max: 20 epochs