fix bugs, see PR or code comments

HRNet.py

@@ -63,7 +63,8 @@ def forward(self, x):
  residual = x
  else: 
  residual = self.shortcut(x)
- out += residual
+ # https://discuss.pytorch.org/t/runtimeerror-one-of-the-variables-needed-for-gradient-computation-has-been-modified-by-an-inplace-operation-torch-floattensor-64-1-which-is-output-0-of-asstridedbackward0-is-at-version-3-expected-version-2-instead-hint-the-backtrace-further-a/171826/7
+ out = out + residual
  out = self.relu(out)
 
  return out

README.md

@@ -15,7 +15,7 @@ this implementation is mainly based on [Deep Camouflage Images](http://zhangqing
 - torchvision
 - tqdm
 - albumentations
-- scikit-learn==0.23.2
+- scikit-learn
 - opencv-contrib
 </details>
 
@@ -89,17 +89,17 @@ For custom images, you should prepare
 ```
 - show_every : interval for displaying intermediate result
 - save_process : If True, save intermediate result by every `show_every`
-- show_comp : compressino ratio for display
+- show_comp : compression ratio for display
 ```
 
 ## Influence by loss function
 According to [Deep Camouflage Images](http://zhangqing-home.net/files/papers/2020/aaai2020.pdf), losses has following impact for generated image:
 
 - style loss : control similarity between generated image and background image
-- camouflage loss : control diffuculty for detection of camouflage objects in generated image
+- camouflage loss : control difficulty for detection of camouflage objects in generated image
  - leave loss : leave foreground features in generated image
  - remove loss : remove foreground features in generated image
-- reguralization loss : control consistency for generated image
+- regularization loss : control consistency for generated image
 - total variation loss : smooth generated image
 
 |style|style+cam|

camouflage_HRNet.py

@@ -14,7 +14,9 @@
 from sklearn.metrics.pairwise import cosine_distances,cosine_similarity
 from sklearn.manifold import LocallyLinearEmbedding
 from sklearn.neighbors import NearestNeighbors
-from sklearn.manifold.locally_linear import barycenter_kneighbors_graph
+# upgrade sklearn to latest version to avoid numpy type deprecation problem
+# new version of sklearn requires to load barycenter_kneighbors_graph from sklearn.manifold._locally_linear
+from sklearn.manifold._locally_linear import barycenter_kneighbors_graph
 
 import HRNet
 from hidden_recommend import recommend

hidden_recommend.py

@@ -43,7 +43,7 @@ def get_MagGrad(gx, gy):
  # Gradient histogram
  def quantization(gradient):
  # prepare quantization table
- gradient_quantized = np.zeros_like(gradient, dtype=np.int)
+ gradient_quantized = np.zeros_like(gradient, dtype=int) # np.int is deprecated after 1.20
 
  # quantization base
  d = np.pi / 9

params_Canyon.py

@@ -2,7 +2,7 @@ class CFG:
  ########################
  #### initial setting ###
  ########################
- input_path="samples/inputs/kuma.png "
+ input_path="samples/inputs/kuma.png"
  mask_path="samples/inputs/kuma_mask.png"
  bg_path="samples/inputs/canyon.png"
  output_dir="samples/outputs/HRNet/Canyon_kuma"

params_Cliff.py

@@ -2,7 +2,7 @@ class CFG:
  ########################
  #### initial setting ###
  ########################
- input_path="samples/inputs/kuma.png "
+ input_path="samples/inputs/kuma.png"
  mask_path="samples/inputs/kuma_mask.png"
  bg_path="samples/inputs/cliff.jpg"
  output_dir="samples/outputs/HRNet/Cliff_kuma"

params_CliffRiver.py

@@ -2,7 +2,7 @@ class CFG:
  ########################
  #### initial setting ###
  ########################
- input_path="samples/inputs/kuma.png "
+ input_path="samples/inputs/kuma.png"
  mask_path="samples/inputs/kuma_mask.png"
  bg_path="samples/inputs/cliff_river.png"
  output_dir="samples/outputs/HRNet/CliffRiver_kuma"

params_Mountain.py

@@ -2,7 +2,7 @@ class CFG:
  ########################
  #### initial setting ###
  ########################
- input_path="samples/inputs/kuma.png "
+ input_path="samples/inputs/kuma.png"
  mask_path="samples/inputs/kuma_mask.png"
  bg_path="samples/inputs/mountain.jpg"
  output_dir="samples/outputs/HRNet/Mountain_kuma"

params_SeaMountain.py

@@ -2,7 +2,7 @@ class CFG:
  ########################
  #### initial setting ###
  ########################
- input_path="samples/inputs/kuma.png "
+ input_path="samples/inputs/kuma.png"
  mask_path="samples/inputs/kuma_mask.png"
  bg_path="samples/inputs/sea_mountain.jpg"
  output_dir="samples/outputs/HRNet/SeaMountain_kuma"

requirements.txt

@@ -1,4 +1,4 @@
 tqdm
 albumentations
 opencv-contrib-python
-scikit-learn==0.23.2
+scikit-learn