Remove DPI adjustment from the data preprocessing

dan/manager/dataset.py

@@ -355,19 +355,6 @@ def apply_preprocessing(sample, preprocessings):
     resize_ratio = [1, 1]
     img = sample["img"]
     for preprocessing in preprocessings:
-        if preprocessing["type"] == "dpi":
-            ratio = preprocessing["target"] / preprocessing["source"]
-            temp_img = img
-            h, w, c = temp_img.shape
-            temp_img = cv2.resize(
-                temp_img, (int(np.ceil(w * ratio)), int(np.ceil(h * ratio)))
-            )
-            if len(temp_img.shape) == 2:
-                temp_img = np.expand_dims(temp_img, axis=2)
-            img = temp_img
-
-            resize_ratio = [ratio, ratio]
-
         if preprocessing["type"] == "to_grayscaled":
             temp_img = img
             h, w, c = temp_img.shape

docs/usage/train/parameters.md

@@ -27,14 +27,6 @@ All hyperparameters are specified and editable in the training scripts (meaning
 Preprocessing is applied before training the network (see `dan/manager/dataset.py`).
 The following transformations are implemented:
 
-* DPI adjustment
-```py
-    {
-        "type": "dpi",
-        "source": 300,
-        "target": 150,
-    }
-```
 * Convert to grayscale
 ```py
 {