(ง •̀_•́)ง we're heading for modeling!

Chunk
1 parent 5c9c44da
Showing 2 changed files with 71 additions and 1 deletions Show diff stats
mdata/ANALYSIS.py
mdata/crop.py
@@ -93,11 +93,28 @@ def anal_0000():
     df_ILS.hist(column='size',bins=100)
     plt.show()
  
+
+
+def pre_crop():
+    df_ILS = pd.read_csv('../res/file-tag-test.tsv', names=['hash', 'width', 'height', 'size', 'quality','chosen','class'], sep='\t')
+    print df_ILS.shape
+    print df_ILS[(df_ILS['width'] >= 300) & (df_ILS['height'] >= 300)].shape
+
+    # 300x300 4213 0.917 *
+    # 200x200 4534 0.987
+    # 400x400 932 0.202
+
+
+
+
 if __name__ == '__main__':
     # anal_ILSVRC()
     # anal_ILSVRC_Test()
-    anal_0000()
+    # anal_0000()
     # print timeit.timeit("anal_ILSVRC()", setup="from __main__ import anal_ILSVRC", number=1)
+
+
+    pre_crop()
     pass
  
  
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+__author__ = 'chunk'
+
+import os, sys
+from PIL import Image
+from common import *
+import random
+
+base_dir = '/data/hadoop/ImageNet/ILSVRC/ILSVRC2013_DET_val/'
+category = 'Test'
+
+
+def crop_Test():
+    for path, subdirs, files in os.walk(os.path.join(base_dir, category)):
+        for name in files:
+            image = os.path.join(path, name)
+            im = Image.open(image)
+            w, h = im.size
+            if w < 300 or h < 300:
+                continue
+            left, upper = random.randint(0, w - 300), random.randint(0, h - 300)
+            im = im.crop((left, upper, left + 300, upper + 300))
+            im.save(os.path.join(base_dir, category + '_crop', name))
+
+
+
+if __name__ == '__main__':
+    timer = Timer()
+
+    timer.mark()
+    crop_Test()
+    timer.report()
+
+    pass
+
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...	...	@@ -93,11 +93,28 @@ def anal_0000():
93	93	df_ILS.hist(column='size',bins=100)
94	94	plt.show()
95	95
	96	+
	97	+
	98	+def pre_crop():
	99	+ df_ILS = pd.read_csv('../res/file-tag-test.tsv', names=['hash', 'width', 'height', 'size', 'quality','chosen','class'], sep='\t')
	100	+ print df_ILS.shape
	101	+ print df_ILS[(df_ILS['width'] >= 300) & (df_ILS['height'] >= 300)].shape
	102	+
	103	+ # 300x300 4213 0.917 *
	104	+ # 200x200 4534 0.987
	105	+ # 400x400 932 0.202
	106	+
	107	+
	108	+
	109	+
96	110	if __name__ == '__main__':
97	111	# anal_ILSVRC()
98	112	# anal_ILSVRC_Test()
99		- anal_0000()
	113	+ # anal_0000()
100	114	# print timeit.timeit("anal_ILSVRC()", setup="from __main__ import anal_ILSVRC", number=1)
	115	+
	116	+
	117	+ pre_crop()
101	118	pass
102	119
103	120
...	...
...	...	@@ -0,0 +1,53 @@
	1	+__author__ = 'chunk'
	2	+
	3	+import os, sys
	4	+from PIL import Image
	5	+from common import *
	6	+import random
	7	+
	8	+base_dir = '/data/hadoop/ImageNet/ILSVRC/ILSVRC2013_DET_val/'
	9	+category = 'Test'
	10	+
	11	+
	12	+def crop_Test():
	13	+ for path, subdirs, files in os.walk(os.path.join(base_dir, category)):
	14	+ for name in files:
	15	+ image = os.path.join(path, name)
	16	+ im = Image.open(image)
	17	+ w, h = im.size
	18	+ if w < 300 or h < 300:
	19	+ continue
	20	+ left, upper = random.randint(0, w - 300), random.randint(0, h - 300)
	21	+ im = im.crop((left, upper, left + 300, upper + 300))
	22	+ im.save(os.path.join(base_dir, category + '_crop', name))
	23	+
	24	+
	25	+
	26	+if __name__ == '__main__':
	27	+ timer = Timer()
	28	+
	29	+ timer.mark()
	30	+ crop_Test()
	31	+ timer.report()
	32	+
	33	+ pass
	34	+
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