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hitokun-s · Apr 2, 2016 · d3e38de · d3e38de
1 parent db4979f
commit d3e38de
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Showing 3 changed files with 97 additions and 8 deletions.
diff --git a/imagenet/food_hack/create_dataset.py b/imagenet/food_hack/create_dataset.py
@@ -170,14 +170,8 @@ def createBboxImage(wnid):
 # bboxデータがあるもの
 # orange
 
-targets = [
-    # "n07722217", # onion
-    # "n07730207", # carrot
-    "n07735510", # pumpkin
-    "n07734017", # tomato
-    "n07747607", # orange
-    "n07739125", # apple
-]
+import targets
+targets = targets.getTargets()
 
 def create(target_wnid):
     get_img_url_with_id(target_wnid)

diff --git a/imagenet/food_hack/resize_and_compute_mean.py b/imagenet/food_hack/resize_and_compute_mean.py
@@ -0,0 +1,86 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+
+import argparse
+import os
+import sys
+
+import numpy
+from PIL import Image
+import six.moves.cPickle as pickle
+
+train_image_dir = "data/bbox_image/"
+
+# ---------------------------------------------------
+# create train.txt
+import targets
+targets = targets.getTargets()
+if os.path.exists("train.txt"):
+    os.remove("train.txt")
+f = open("train.txt","w")
+for fileName in os.listdir(train_image_dir):
+    image_id = fileName[:fileName.index(".")]
+    if image_id in targets:
+        classIdx = targets.index(image_id)
+        f.write((train_image_dir + "%s %d") % (fileName, classIdx) + "\n")
+f.close()
+# ---------------------------------------------------
+
+# ---------------------------------------------------
+# resize
+print "====================================="
+print "start resize!"
+print "====================================="
+for i, imgpath in enumerate(os.listdir(train_image_dir)):
+    if not imgpath.endswith(".jpg"):
+        print "not image file!:%s" % imgpath
+        continue
+    print i
+    img = Image.open(train_image_dir + imgpath)
+    size = min(img.size) # img.size は、(width, height)というタプルを返す。PILのバージョンによっては、img.width, img.heightも使えるが。
+    start_x = img.size[0] / 2 - size / 2
+    start_y = img.size[1] / 2 - size / 2
+    box = (start_x, start_y, start_x + size, start_y + size) #  box is a 4-tuple defining the left, upper, right, and lower pixel coordinate.
+    img2 = img.crop(box).resize((256, 256), Image.ANTIALIAS)
+    img2.save(train_image_dir + imgpath, 'JPEG')
+
+# -----------------------------------------------------
+
+parser = argparse.ArgumentParser(description='Compute images mean array')
+parser.add_argument('--dataset', '-d', help='Path to training image-label list file',  default='train.txt')
+parser.add_argument('--root', '-r', default='.',
+                    help='Root directory path of image files')
+parser.add_argument('--output', '-o', default='mean.npy',
+                    help='path to output mean array')
+args = parser.parse_args()
+
+sum_image = None
+count = 0
+for i, line in enumerate(open(args.dataset)):
+    filepath = os.path.join(args.root, line.strip().split()[0])
+    if not filepath.endswith(".jpg"):
+        print "not jpg file. skip..."
+        continue
+    try:
+        image = numpy.asarray(Image.open(filepath)).transpose(2, 0, 1)
+    except:
+        print "idx:%d" % i
+        print "file:%s" % filepath
+        print sys.exc_info()[0]
+        continue
+
+    if sum_image is None:
+        sum_image = numpy.ndarray(image.shape, dtype=numpy.float32)
+        sum_image[:] = image
+    else:
+        # ここで、operands could not be broadcast together with shapes エラーになった
+        # broadcast ... サイズ/形状の異なる配列同士の演算のこと
+        sum_image += image
+    count += 1
+    # sys.stderr.write('\r{}'.format(count))
+    # sys.stderr.flush()
+
+sys.stderr.write('\n')
+
+mean = sum_image / count
+pickle.dump(mean, open(args.output, 'wb'), -1)
diff --git a/imagenet/food_hack/targets.py b/imagenet/food_hack/targets.py
@@ -0,0 +1,9 @@
+def getTargets():
+    return [
+        # "n07722217", # onion
+        # "n07730207", # carrot
+        "n07735510", # pumpkin
+        "n07734017", # tomato
+        "n07747607", # orange
+        "n07739125", # apple
+    ]