From 684351b6b12fa8f2927d2d3695928ba5e0a40973 Mon Sep 17 00:00:00 2001
From: manonBlanco <blanco@teklia.com>
Date: Mon, 12 Jun 2023 15:26:51 +0200
Subject: [PATCH] Remove DPIAdjusting transform
---
dan/transforms.py | 49 +---------------------------------
docs/usage/train/parameters.md | 8 ------
2 files changed, 1 insertion(+), 56 deletions(-)
diff --git a/dan/transforms.py b/dan/transforms.py
index 2c596e3c..00bd6385 100644
--- a/dan/transforms.py
+++ b/dan/transforms.py
@@ -20,22 +20,6 @@ from torchvision.transforms import (
from torchvision.transforms.functional import InterpolationMode
-class DPIAdjusting:
- """
- Resolution modification
- """
-
- def __init__(self, factor):
- self.factor = factor
-
- def __call__(self, x):
- w, h = x.size
- return x.resize(
- (int(np.ceil(w * self.factor)), int(np.ceil(h * self.factor))),
- Image.BILINEAR,
- )
-
-
class Dilation:
"""
OCR: stroke width increasing
@@ -175,33 +159,8 @@ def get_list_augmenters(img, aug_configs, fill_value):
for aug_config in aug_configs:
if rand((1,)) > aug_config["proba"]:
continue
- if aug_config["type"] == "dpi":
- valid_factor = False
- while not valid_factor:
- factor = Uniform(
- aug_config["min_factor"], aug_config["max_factor"]
- ).sample()
- valid_factor = not (
- (
- "max_width" in aug_config
- and factor * img.size[0] > aug_config["max_width"]
- )
- or (
- "max_height" in aug_config
- and factor * img.size[1] > aug_config["max_height"]
- )
- or (
- "min_width" in aug_config
- and factor * img.size[0] < aug_config["min_width"]
- )
- or (
- "min_height" in aug_config
- and factor * img.size[1] < aug_config["min_height"]
- )
- )
- augmenters.append(DPIAdjusting(factor))
- elif aug_config["type"] == "zoom_ratio":
+ if aug_config["type"] == "zoom_ratio":
ratio_h = Uniform(
aug_config["min_ratio_h"], aug_config["max_ratio_h"]
).sample()
@@ -340,12 +299,6 @@ def aug_config(proba_use_da, p):
"order": "random",
"proba": proba_use_da,
"augmentations": [
- {
- "type": "dpi",
- "proba": p,
- "min_factor": 0.75,
- "max_factor": 1,
- },
{
"type": "perspective",
"proba": p,
diff --git a/docs/usage/train/parameters.md b/docs/usage/train/parameters.md
index 9674f06c..e1dc0736 100644
--- a/docs/usage/train/parameters.md
+++ b/docs/usage/train/parameters.md
@@ -85,7 +85,6 @@ Augmentation transformations are applied on-the-fly during training to artificia
The following transformations are implemented in `dan/transforms.py`:
* Color inversion
-* DPI adjusting
* Dilation and erosion
* Elastic distortion
* Reducing interline spacing
@@ -105,13 +104,6 @@ The following configuration is used by default when using the `teklia-dan train
"order": "random",
"proba": 0.9,
"augmentations": [
- {
- "type": "dpi",
- "proba": 0.1,
- "min_factor": 0.75,
- "max_factor": 1,
- "preserve_ratio": True,
- },
{
"type": "perspective",
"proba": 0.1,
--
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