Support for testing with tox

README.md

@@ -12,14 +12,40 @@ The above will save each image class in a separate subdirectory under the base
 directory, with images in a subdirectory named "images" and the PASCAL VOC format 
 annotations in a subdirectory named "pascal".
 
+## Resize images
+In order to resize images and update the associated annotations use the script 
+`cvdata/resize.py`. This script currently supports annotations in KITTI (*.txt) 
+and PASCAL VOC (*.xml) formats. For example to resize images to 1024x768 and 
+update the associated annotations in KITTI format:
+```bash
+$ python resize.py --input_images /ssd_training/kitti/image_2 \
+    --input_annotations /ssd_training/kitti/label_2 \
+    --output_images /ssd_training/kitti/image_2 \
+    --output_annotations /ssd_training/kitti/label_2 \
+    --width 1024 --height 768 --format kitti
+```
+
+## Convert annotation formats
+In order to convert from one annotation format to another use the script 
+`cvdata/convert.py`. This script currently supports converting annotations from 
+PASCAL to KITTI formats. For example: 
+```bash
+$ python convert.py --in_format pascal --out_format kitti \
+    --annotations_dir /data/handgun/pascal \
+    --images_dir /data/handgun/images \
+    --out_dir /data/handgun/kitti \
+    --kitti_ids_file handgun.txt
+``` 
+
 ## Rename annotation labels
 In order to rename the image class labels of annotations use the script 
-`cvdata/visualize.py`. This script currently supports annotations in KITTI (*.txt) 
+`cvdata/rename.py`. This script currently supports annotations in KITTI (*.txt) 
 and PASCAL VOC (*.xml) formats. It is used to replace the label name for all 
 annotation files of the specified format in the specified directory. For example:
 ```bash
 $ python rename.py --labels_dir /data/cvdata/pascal --old handgun --new firearm --format pascal
 ```
+
 ## Visualize annotations
 In order to visualize images and corresponding annotations use the script 
 `cvdata/visualize.py`. This script currently supports annotations in COCO (*.json), 

requirements.txt

@@ -0,0 +1,30 @@
+boto3==1.10.28
+botocore==1.13.28
+certifi==2019.9.11
+chardet==3.0.4
+docutils==0.15.2
+filelock==3.0.10
+idna==2.8
+importlib-metadata==0.23
+jmespath==0.9.4
+lxml==4.4.2
+more-itertools==7.2.0
+numpy==1.17.4
+opencv-python==4.1.2.30
+packaging==19.2
+pandas==0.25.3
+Pillow==6.2.1
+pluggy==0.12.0
+py==1.8.0
+pyparsing==2.4.5
+python-dateutil==2.8.0
+pytz==2019.3
+requests==2.22.0
+s3transfer==0.2.1
+six==1.13.0
+toml==0.10.0
+tox==3.14.1
+tqdm==4.39.0
+urllib3==1.25.7
+virtualenv==16.7.5
+zipp==0.6.0

setup.py

@@ -8,14 +8,14 @@
 
 setuptools.setup(
     name="cvdata",
-    version="0.0.1",
+    version="0.0.2",
     author="James Adams",
     author_email="monocongo@gmail.com",
     description="Tools for creating and manipulating computer vision datasets",
     long_description=long_description,
     long_description_content_type="text/markdown",
     url="https://github.com/monocongo/cvdata",
-    python_requires=">=3.0, <3.8",
+    python_requires=">=3.0",
     packages=[
         "cvdata",
     ],
@@ -30,15 +30,11 @@
         "boto3",
         "lxml",
         "numpy",
-        "opencv-contrib-python-nonfree",
+        "opencv-python",
+        # "opencv-contrib-python-nonfree",
         "pandas",
         "pillow",
         "requests",
         "tqdm",
     ],
-    tests_require=[
-        "opencv",
-        "pytest",
-        "scikit-image",
-    ]
 )

tests/assert_utils.py

@@ -1,10 +1,8 @@
-import cv2
-# scikit-image version <0.16
-from skimage.measure import compare_mse as mean_squared_error
-# scikit-image version >=0.16
-# from skimage.metrics import mean_squared_error
 from xml.etree import ElementTree
 
+import cv2
+from skimage.metrics import mean_squared_error
+
 
 # ------------------------------------------------------------------------------
 def elements_equal(e1, e2) -> bool:

tests/test_clean.py

@@ -1,15 +1,10 @@
 import logging
 import os
 
-import cv2
 import pytest
-# scikit-image version <0.16
-from skimage.measure import compare_mse as mean_squared_error
-# scikit-image version >=0.16
-# from skimage.metrics import mean_squared_error
 
 from cvdata import clean
-from tests.assert_utils import images_equal, xml_equal
+from assert_utils import images_equal, xml_equal
 
 # ------------------------------------------------------------------------------
 # disable logging messages

tests/test_convert.py

@@ -9,7 +9,7 @@
 # from skimage.metrics import mean_squared_error
 
 from cvdata import convert
-from tests.assert_utils import images_equal
+from assert_utils import images_equal
 
 
 # ------------------------------------------------------------------------------

tests/test_relabel.py

@@ -4,7 +4,7 @@
 import pytest
 
 from cvdata import relabel
-from tests.assert_utils import elements_equal, text_files_equal
+from assert_utils import elements_equal, text_files_equal
 
 # ------------------------------------------------------------------------------
 # disable logging messages

tests/test_resize.py

@@ -6,7 +6,7 @@
 import pytest
 
 from cvdata import resize
-from tests.assert_utils import text_files_equal, xml_equal
+from assert_utils import text_files_equal, xml_equal
 
 # ------------------------------------------------------------------------------
 # disable logging messages

tox.ini

@@ -0,0 +1,8 @@
+[tox]
+envlist = py3
+
+[testenv]
+deps = opencv-python
+    pytest
+    scikit-image
+commands = pytest