Optimize directory structure. Add img_decoder module.

README.md

@@ -7,7 +7,9 @@ PaddleRS是基于飞桨的遥感影像处理平台，支持遥感图像分类，
 - [ ] 多光谱、高光谱、SAR、无人机RGBD
 - [ ] 数据切分、合并、通道提取等功能
 - [ ] 支持任意通道数据增强策略
-  
+- [ ] 支持多种遥感影像格式  
+遥感影像的格式多种多样，不同传感器产生的数据格式也可能不同。PaddleRS现已兼容6+种格式图片读取：`tif`, `png`, `jpeg`, `bmp`, `img`, `npy`.
+
 ### 算法模型
 - [ ] 分类（ResNet，MobileNet，HRNet）
 - [ ] 检测（PP-YOLO，Faster-RCNN，S2ANet）
@@ -22,4 +24,4 @@ PaddleRS是基于飞桨的遥感影像处理平台，支持遥感图像分类，
 - [ ] 构建各场景的预训练模型，如建筑物、河流、植被等
 
 ### 应用示例
-- [ ] 场景范例库，指导用户完成模型的构建，完成模型落地
+- [ ] 场景范例库，指导用户完成模型的构建，完成模型落地

paddlers/__init__.py

@@ -0,0 +1 @@
+from . import datasets, transforms, utils, tools

paddlers/transforms/img_decoder.py

@@ -0,0 +1,158 @@
+
+   
+# copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#    http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import numpy as np
+import os.path as osp
+import cv2
+import copy
+import random
+import imghdr
+from PIL import Image
+try:
+    from collections.abc import Sequence
+except Exception:
+    from collections import Sequence
+
+# from paddlers.transforms.operators import Transform
+
+
+class Transform(object):
+    """
+    Parent class of all data augmentation operations
+    """
+
+    def __init__(self):
+        pass
+
+    def apply_im(self, image):
+        pass
+
+    def apply_mask(self, mask):
+        pass
+
+    def apply_bbox(self, bbox):
+        pass
+
+    def apply_segm(self, segms):
+        pass
+
+    def apply(self, sample):
+        sample['image'] = self.apply_im(sample['image'])
+        if 'mask' in sample:
+            sample['mask'] = self.apply_mask(sample['mask'])
+        if 'gt_bbox' in sample:
+            sample['gt_bbox'] = self.apply_bbox(sample['gt_bbox'])
+
+        return sample
+
+    def __call__(self, sample):
+        if isinstance(sample, Sequence):
+            sample = [self.apply(s) for s in sample]
+        else:
+            sample = self.apply(sample)
+
+        return sample
+
+
+class ImgDecode(Transform):
+    """
+    Decode image(s) in input.
+    Args:
+        to_rgb (bool, optional): If True, convert input images from BGR format to RGB format. Defaults to True.
+    """
+
+    def __init__(self, to_rgb=True):
+        super(ImgDecode, self).__init__()
+        self.to_rgb = to_rgb
+
+    def read_img(self, img_path, input_channel=3):
+        img_format = imghdr.what(img_path)
+        name, ext = osp.splitext(img_path)
+        if img_format == 'tiff' or ext == '.img':
+            try:
+                import gdal
+            except:
+                try:
+                    from osgeo import gdal
+                except:
+                    raise Exception(
+                        "Failed to import gdal! You can try use conda to install gdal"
+                    )
+                    six.reraise(*sys.exc_info())
+
+            dataset = gdal.Open(img_path)
+            if dataset == None:
+                raise Exception('Can not open', img_path)
+            im_data = dataset.ReadAsArray()
+            return im_data.transpose((1, 2, 0))
+        elif img_format in ['jpeg', 'bmp', 'png', 'jpg']:
+            if input_channel == 3:
+                return cv2.imread(img_path, cv2.IMREAD_ANYDEPTH |
+                                  cv2.IMREAD_ANYCOLOR | cv2.IMREAD_COLOR)
+            else:
+                return cv2.imread(im_file, cv2.IMREAD_ANYDEPTH |
+                                  cv2.IMREAD_ANYCOLOR)
+        elif ext == '.npy':
+            return np.load(img_path)
+        else:
+            raise Exception('Image format {} is not supported!'.format(ext))
+
+    def apply_im(self, im_path):
+        if isinstance(im_path, str):
+            try:
+                image = self.read_img(im_path)
+            except:
+                raise ValueError('Cannot read the image file {}!'.format(
+                    im_path))
+        else:
+            image = im_path
+
+        if self.to_rgb:
+            image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+
+        return image
+
+    def apply_mask(self, mask):
+        try:
+            mask = np.asarray(Image.open(mask))
+        except:
+            raise ValueError("Cannot read the mask file {}!".format(mask))
+        if len(mask.shape) != 2:
+            raise Exception(
+                "Mask should be a 1-channel image, but recevied is a {}-channel image.".
+                format(mask.shape[2]))
+        return mask
+
+    def apply(self, sample):
+        """
+        Args:
+            sample (dict): Input sample, containing 'image' at least.
+        Returns:
+            dict: Decoded sample.
+        """
+        sample['image'] = self.apply_im(sample['image'])
+        if 'mask' in sample:
+            sample['mask'] = self.apply_mask(sample['mask'])
+            im_height, im_width, _ = sample['image'].shape
+            se_height, se_width = sample['mask'].shape
+            if im_height != se_height or im_width != se_width:
+                raise Exception(
+                    "The height or width of the im is not same as the mask")
+
+        sample['im_shape'] = np.array(
+            sample['image'].shape[:2], dtype=np.float32)
+        sample['scale_factor'] = np.array([1., 1.], dtype=np.float32)
+        return sample