Fix couple of bugs, bump the version. (#11)

README.md

@@ -35,10 +35,12 @@ pip install image-similarity-measures
 #### Evaluation
 For doing the evaluation, you can easily run the following command:
 ```bash
-imagery-similarity-measures --org_img_path=path_to_first_img --pred_img_path=path_to_second_img --mode=tif
+image-similarity-measures --org_img_path=path_to_first_img --pred_img_path=path_to_second_img --mode=tif
 ```
 If you want to save the final result in a file you can add `--write_to_file` at then end of above command.
 
+**Note** that images that are used for evaluation should be **channel last**.
+
 #### Usage in python
 ```bash
 import image_similarity_measures

image_similarity_measures/evaluate.py

@@ -56,7 +56,7 @@ def write_final_dict(metric, metric_dict):
         f.writelines('{}\n'.format(v) for _, v in metric_dict.items())
 
 
-def evaluation(org_img_path, pred_img_path, mode, write_to_file):
+def evaluation(org_img_path, pred_img_path, mode, metric, write_to_file):
     metric_dict = {}
 
     if mode == "tif":
@@ -98,7 +98,7 @@ def main():
     mode = args.mode
     write_to_file = args.write_to_file
 
-    evaluation(orgpath, predpath, mode, write_to_file)
+    evaluation(orgpath, predpath, mode, metric, write_to_file)
 
 if __name__ == "__main__":
     main()

image_similarity_measures/quality_metrics.py

@@ -17,15 +17,15 @@ def _assert_image_shapes_equal(org_img: np.ndarray, pred_img: np.ndarray, metric
     assert org_img.shape == pred_img.shape, msg
 
 
-def rmse(org_img: np.ndarray, pred_img: np.ndarray):
+def rmse(org_img: np.ndarray, pred_img: np.ndarray, data_range=4096):
     """
     Root Mean Squared Error
     """
 
     _assert_image_shapes_equal(org_img, pred_img, "RMSE")
     rmse_final = []
     for i in range(org_img.shape[2]):
-        m = np.mean((org_img[:, :, i] - pred_img[:, :, i]) ** 2)
+        m = np.mean(((org_img[:, :, i] - pred_img[:, :, i]) / data_range) ** 2)
         s = np.sqrt(m)
         rmse_final.append(s)
     return np.mean(rmse_final)
@@ -188,6 +188,7 @@ def uiq(org_img: np.ndarray, pred_img: np.ndarray):
     """
     Universal Image Quality index
     """
+    # TODO: Apply optimization, right now it is very slow
     _assert_image_shapes_equal(org_img, pred_img, "UIQ")
     q_all = []
     for (x, y, window_org), (x, y, window_pred) in zip(sliding_window(org_img, stepSize=1, windowSize=(8, 8)),

setup.py

@@ -5,7 +5,7 @@
 
 setuptools.setup(
     name="image-similarity-measures",
-    version="0.1.1",
+    version="0.1.2",
     author="UP42",
     author_email="[email protected]",
     description="Evaluation metrics to assess the similarity between two images.",