Cleaned up unused imports and PEP8 stuff

exsprite/core/sprite_sheet.py

@@ -1,17 +1,10 @@
 import os
-import math
+from functools import reduce
 import numpy as np
 from skimage import io
-from skimage.exposure import histogram
-from skimage.measure import label
-from skimage.segmentation import flood, flood_fill
-from scipy import ndimage
+from skimage.segmentation import flood
 from scipy.ndimage.measurements import label
-from functools import reduce
-from PIL import Image
-import cv2
-import fire
-from exsprite.utils import show, unique, filter_bounds, get_bounds, transpose
+from exsprite.utils import unique, filter_bounds, get_bounds, transpose
 
 
 def get_chunk(tup, labeled):
@@ -29,7 +22,7 @@ def get_labeled_for_rows(labeled, row_tups):
  max_row = []
  chunk = get_chunk(tup, labeled)
  chunk_set = get_chunk_set(chunk)
- sorted_rows = sorted(chunk, key=lambda x: len(x), reverse=True)
+ sorted_rows = sorted(chunk, key=len, reverse=True)
  if not sorted_rows:
  continue
  while set(max_row) != chunk_set:
@@ -44,13 +37,13 @@ def __init__(self, filepath, folderpath=None, background=0, group='row'):
  self.filepath = filepath
  self.folderpath = folderpath if folderpath else f"{filepath.split('.')[0]}_groups"
  self.img = io.imread(filepath)
- self.group=group
- if self.group=='col':
- self.img=transpose(self.img)
- self.background=background
- self.boolean_image=None
- self.num_labels=None
- self.labeled_image=None
+ self.group = group
+ if self.group == 'col':
+ self.img = transpose(self.img)
+ self.background = background
+ self.boolean_image = None
+ self.num_labels = None
+ self.labeled_image = None
  self._get_boolean_image()
  self._get_labeled_image()
 
@@ -84,13 +77,13 @@ def save(self):
  for group_num, group in enumerate(sprite_groups):
  group_folderpath = f"{self.folderpath}/{self.group}_{group_num}"
  self._check_create_folder(group_folderpath)
- for i, label in enumerate(group):
+ for i, label_num in enumerate(group):
  filepath = f"{group_folderpath}/{self.group}{group_num}_{i}.png"
- raw_inds = np.where(self.labeled_image==label)
+ raw_inds = np.where(self.labeled_image == label_num)
  rrow, rcol = raw_inds
  minr, maxr = int(min(rrow)), int(max(rrow))
  minc, maxc = int(min(rcol)), int(max(rcol))
- sub_image = self.img[minr:maxr+1,minc:maxc+1]
- if self.group=='col':
+ sub_image = self.img[minr:maxr+1, minc:maxc+1]
+ if self.group == 'col':
  sub_image = transpose(sub_image)
- io.imsave(filepath,sub_image,check_contrast=False)
+ io.imsave(filepath, sub_image, check_contrast=False)

exsprite/utils/utils.py

@@ -1,14 +1,13 @@
 import matplotlib.pyplot as plt
 import numpy as np
-from skimage import io, data, filters
+from skimage import io
 
 def transpose(img_array):
  return np.array([list(i) for i in zip(*img_array)])
 
 def centroid(t1,t2):
  return (int(sum(t1)/2), int(sum(t2)/2))
 
-# Todo refactor to check set of sets for largest then retrieve row
 def unique(array, ignore=[0]):
  ignore = set(ignore)
  seen = set()
@@ -43,4 +42,4 @@ def filter_bounds(bounds):
  return bound_nums
 
 def get_bounds(int_img):
- return [i for i, row in enumerate(int_img) if not sum(row)]
+ return [i for i, row in enumerate(int_img) if not sum(row)]

setup.py

@@ -7,13 +7,11 @@
  readme = readme_file.read()
 
 requirements = ['numpy',
- 'Pillow',
  'scikit-image',
  'scipy',
- 'opencv-python',
  'fire',
  'matplotlib'
- ]
+  ]
 
 setup(
  author="Ryan Sudhakaran",
@@ -38,4 +36,4 @@
  url='https://github.com/rysuds/exsprite',
  version='0.1.0',
  zip_safe=False,
-)
+)