add picodet tutorial

paddlex/cv/models/detector.py

@@ -713,6 +713,7 @@ class PicoDet(BaseDetector):
             model_name='PicoDet', num_classes=num_classes, **params)
 
     def _compose_batch_transform(self, transforms, mode='train'):
+        default_batch_transforms = [_BatchPadding(pad_to_stride=32)]
         if mode == 'eval':
             collate_batch = True
         else:
@@ -729,7 +730,8 @@ class PicoDet(BaseDetector):
                 custom_batch_transforms.insert(0, copy.deepcopy(op))
 
         batch_transforms = BatchCompose(
-            custom_batch_transforms, collate_batch=collate_batch)
+            custom_batch_transforms + default_batch_transforms,
+            collate_batch=collate_batch)
 
         return batch_transforms
 

tutorials/train/object_detection/picodet.py

@@ -0,0 +1,58 @@
+import paddlex as pdx
+from paddlex import transforms as T
+
+# 下载和解压昆虫检测数据集
+dataset = 'https://bj.bcebos.com/paddlex/datasets/insect_det.tar.gz'
+pdx.utils.download_and_decompress(dataset, path='./')
+
+# 定义训练和验证时的transforms
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/transforms/transforms.md
+train_transforms = T.Compose([
+    T.RandomCrop(), T.RandomHorizontalFlip(), T.RandomDistort(),
+    T.BatchRandomResize(
+        target_sizes=[576, 608, 640, 672, 704], interp='RANDOM'), T.Normalize(
+            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+])
+
+eval_transforms = T.Compose([
+    T.Resize(
+        target_size=640, interp='CUBIC'), T.Normalize(
+            mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
+])
+
+# 定义训练和验证所用的数据集
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/datasets.md
+train_dataset = pdx.datasets.VOCDetection(
+    data_dir='insect_det',
+    file_list='insect_det/train_list.txt',
+    label_list='insect_det/labels.txt',
+    transforms=train_transforms,
+    shuffle=True)
+
+eval_dataset = pdx.datasets.VOCDetection(
+    data_dir='insect_det',
+    file_list='insect_det/val_list.txt',
+    label_list='insect_det/labels.txt',
+    transforms=eval_transforms,
+    shuffle=False)
+
+# 初始化模型，并进行训练
+# 可使用VisualDL查看训练指标，参考https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/visualdl.md
+num_classes = len(train_dataset.labels)
+model = pdx.det.PicoDet(num_classes=num_classes, backbone='ESNet_l')
+
+# API说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/apis/models/detection.md
+# 各参数介绍与调整说明：https://github.com/PaddlePaddle/PaddleX/blob/develop/docs/parameters.md
+model.train(
+    num_epochs=300,
+    train_dataset=train_dataset,
+    train_batch_size=7,
+    eval_dataset=eval_dataset,
+    pretrain_weights='COCO',
+    learning_rate=.05,
+    warmup_steps=300,
+    warmup_start_lr=0.0,
+    save_interval_epochs=5,
+    lr_decay_epochs=[85, 135],
+    save_dir='output/piconet_esnet_l',
+    use_vdl=True)