Merge pull request #38 from heavengate/fix_yolo_backbone

fix yolo backbone

examples/yolov3/.gitignore

 dataset/voc*
+pretrain_weights/darknet53_pretrained.pdparams

examples/yolov3/README.md

@@ -99,12 +99,17 @@ YOLOv3 的网络结构由基础特征提取网络、multi-scale特征融合层
   |   ...
   ```
 
+```bash
+sh pretrain_weights/download.sh
+```
+
 ### 模型训练
 
-数据准备完毕后，可使用`main.py`脚本启动训练和评估，如下脚本会自动每epoch交替进行训练和模型评估，并将checkpoint默认保存在`yolo_checkpoint`目录下。
+数据准备完成后，可使用`main.py`脚本启动训练和评估，如下脚本会自动每epoch交替进行训练和模型评估，并将checkpoint默认保存在`yolo_checkpoint`目录下。
 
 YOLOv3模型训练总batch_size为64训练，以下以使用4卡Tesla P40每卡batch_size为16训练介绍训练方式。对于静态图和动态图，多卡训练中`--batch_size`为每卡上的batch_size，即总batch_size为`--batch_size`乘以卡数。
 
+YOLOv3模型训练须加载骨干网络[DarkNet53]()的预训练权重，可在训练时通过`--pretrain_weights`指定，若指定为URL，将自动下载权重至`~/.cache/paddle/weights`目录并加载。
 
 `main.py`脚本参数可通过如下命令查询
 
@@ -117,7 +122,7 @@ python main.py --help
 使用如下方式进行多卡训练:
 
 ```bash
-CUDA_VISIBLE_DEVICES=0,1,2,3 python -m paddle.distributed.launch main.py --data=<path/to/dataset> --batch_size=16
+CUDA_VISIBLE_DEVICES=0,1,2,3 python -m paddle.distributed.launch main.py --data=<path/to/dataset> --batch_size=16 --pretrain_weights=https://paddlemodels.bj.bcebos.com/hapi/darknet53_pretrained.pdparams
 ```
 
 #### 动态图训练
@@ -127,7 +132,7 @@ CUDA_VISIBLE_DEVICES=0,1,2,3 python -m paddle.distributed.launch main.py --data=
 使用如下方式进行多卡训练:
 
 ```bash
-CUDA_VISIBLE_DEVICES=0,1,2,3 python main.py -m paddle.distributed.launch --data=<path/to/dataset> --batch_size=16 -d
+CUDA_VISIBLE_DEVICES=0,1,2,3 python main.py -m paddle.distributed.launch --data=<path/to/dataset> --batch_size=16 -d --pretrain_weights=https://paddlemodels.bj.bcebos.com/hapi/darknet53_pretrained.pdparams
 ```
 
 

examples/yolov3/main.py

@@ -27,6 +27,7 @@ from paddle.io import DataLoader
 
 from hapi.model import Model, Input, set_device
 from hapi.distributed import DistributedBatchSampler
+from hapi.download import is_url, get_weights_path
 from hapi.datasets import COCODataset
 from hapi.vision.transforms import *
 from hapi.vision.models import yolov3_darknet53, YoloLoss
@@ -124,8 +125,11 @@ def main():
                    model_mode='eval' if FLAGS.eval_only else 'train',
                    pretrained=pretrained)
 
-    if FLAGS.pretrain_weights is not None:
-        model.load(FLAGS.pretrain_weights, skip_mismatch=True, reset_optimizer=True)
+    if FLAGS.pretrain_weights and not FLAGS.eval_only:
+        pretrain_weights = FLAGS.pretrain_weights
+        if is_url(pretrain_weights):
+            pretrain_weights = get_weights_path(pretrain_weights)
+        model.load(pretrain_weights, skip_mismatch=True, reset_optimizer=True)
 
     optim = make_optimizer(len(batch_sampler), parameter_list=model.parameters())
 
@@ -196,7 +200,8 @@ if __name__ == '__main__':
     parser.add_argument(
         "-j", "--num_workers", default=4, type=int, help="reader worker number")
     parser.add_argument(
-        "-p", "--pretrain_weights", default=None, type=str,
+        "-p", "--pretrain_weights",
+        default="./pretrain_weights/darknet53_pretrained", type=str,
         help="path to pretrained weights")
     parser.add_argument(
         "-r", "--resume", default=None, type=str,

hapi/download.py

@@ -29,13 +29,22 @@ from paddle.fluid.dygraph.parallel import ParallelEnv
 import logging
 logger = logging.getLogger(__name__)
 
-__all__ = ['get_weights_path']
+__all__ = ['get_weights_path', 'is_url']
 
 WEIGHTS_HOME = osp.expanduser("~/.cache/paddle/hapi/weights")
 
 DOWNLOAD_RETRY_LIMIT = 3
 
 
+def is_url(path):
+    """
+    Whether path is URL.
+    Args:
+        path (string): URL string or not.
+    """
+    return path.startswith('http://') or path.startswith('https://')
+
+
 def get_weights_path(url, md5sum=None):
     """Get weights path from WEIGHT_HOME, if not exists,
     download it from url.
@@ -62,6 +71,7 @@ def get_path(url, root_dir, md5sum=None, check_exist=True):
                     WEIGHTS_HOME or DATASET_HOME
     md5sum (str): md5 sum of download package
     """
+    assert is_url(url), "downloading from {} not a url".format(url)
     # parse path after download to decompress under root_dir
     fullpath = map_path(url, root_dir)
 

hapi/model.py

@@ -798,6 +798,13 @@ class Model(fluid.dygraph.Layer):
                     format(key, list(state.shape), list(param.shape)))
             return param, state
 
+	def _strip_postfix(path):
+	    path, ext = os.path.splitext(path)
+	    assert ext in ['', '.pdparams', '.pdopt', '.pdmodel'], \
+		    "Unknown postfix {} from weights".format(ext)
+	    return path
+
+        path = _strip_postfix(path)
         param_state = _load_state_from_path(path + ".pdparams")
         assert param_state, "Failed to load parameters, please check path."
 

hapi/vision/models/darknet.py

@@ -136,7 +136,7 @@ class LayerWarp(fluid.dygraph.Layer):
 DarkNet_cfg = {53: ([1, 2, 8, 8, 4])}
 
 
-class DarkNet(Model):
+class DarkNet(fluid.dygraph.Layer):
     """DarkNet model from
     `"YOLOv3: An Incremental Improvement" <https://arxiv.org/abs/1804.02767>`_
 

hapi/vision/models/yolov3.py

@@ -118,7 +118,7 @@ class YOLOv3(Model):
         self.nms_posk = 100
         self.draw_thresh = 0.5
 
-        self.backbone = darknet53(pretrained=(model_mode=='train'))
+        self.backbone = darknet53(pretrained=False)
         self.block_outputs = []
         self.yolo_blocks = []
         self.route_blocks = []