make pkg work with python 3.7

.github/workflows/python-app.yml

@@ -8,17 +8,19 @@ on:
     branches: [master]
   pull_request:
     branches: [master]
-
 jobs:
   build:
     runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ["3.7", "3.8", "3.9"]
 
     steps:
       - uses: actions/checkout@v2
-      - name: Set up Python 3.8.10
+      - name: Set up Python ${{ matrix.python-version }}
         uses: actions/setup-python@v2
         with:
-          python-version: 3.8.10
+          python-version: ${{ matrix.python-version }}
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip

Makefile

@@ -59,7 +59,7 @@ create_environment:
 ifeq (True,$(HAS_CONDA))
 		@echo ">>> Detected conda, creating conda environment."
 ifeq (3,$(findstring 3,$(PYTHON_INTERPRETER)))
-	conda create --name $(PROJECT_NAME) python=3
+	conda create --name $(PROJECT_NAME) python=3.8
 else
 	conda create --name $(PROJECT_NAME) python=2.7
 endif

README.md

@@ -4,6 +4,11 @@ Provide good support for deep learning and computer vision tasks by creating a t
 
 Here is a sample image pairs, the size of RGB and GT are 1000-by-1000 large. The `SplitRaster` package successfully generate 16 256x256 images tiles with automatic padding on the edges. You can adjust the tile size and the overlap of the tiles for your own applications.
 
+
+## Update Log
+- 2022-Jan-16  Fix bugs to make package suitable for python 3.7. Publish new version at(https://pypi.org/project/splitraster/0.3.2/) .
+
+
 ![Sample Image](docs/split_raster_sample.png)
 
 ## Use the packages

requirements.txt

@@ -14,4 +14,4 @@
 # GDAL==3.3.1
 # tqdm>=4.40.0
 # scikit-image>=0.18.0
-splitraster==0.3.1
+splitraster==0.3.2

setup.py

@@ -2,7 +2,7 @@
 from pathlib import Path
 setup(
     name='splitraster',
-    version='0.3.1',
+    version='0.3.2',
     author='Chris Cui',
     author_email='',
     description='Provide good support for deep learning and computer vision tasks by creating a tiled output from an input raster dataset.',

src/splitraster/io.py

@@ -82,7 +82,7 @@ def split_image(img_path, save_path, crop_size, repetition_rate=0, overwrite=Tru
     print(f"Input Image File Shape (H, W, D):{ img.shape}")
 
     stride = int(crop_size*(1-repetition_rate))
-    print(f"{crop_size=}, {stride=}")
+    print(f"crop_size = {crop_size}, stride = {stride}")
 
     padded_img = padding_image(img,   stride)
     H = padded_img.shape[0]