def train():
path = "./submission/snapshots/training/"
images = {}
i = 0
number_correct = 0
for root, dirs, filenames in os.walk(path):
for f in filenames:
#if f=="104lady.png":
if i < 9000:
#if "tree" in f:
print "Loading image", f
images[f] = classifier.load_image(path+f)
i = i+1
f = None
if WRITE_TO_FILE:
f = open("training_results.txt", "w")
for image in images:
print "\n--------------------------------------------- PARSING IMAGE", image
image_list = images[image]
edge_array = image_list[0]
segments = get_segments_from_edges(edge_array)
x_ranges = find_object_x_ranges(segments)
obj_num = 1
for range in x_ranges:
obj_num +=1
print "------------------ IDENTIFYING OBJECT %s OF %s ------------------" % (obj_num, len(x_ranges))
range_segments = find_segments_in_range(range, segments)
total_segment_length = length_of_all_segments(range_segments)
if len(range_segments) <= 1:
print "Object disregarded, only contains one path"
elif total_segment_length < 50:
print "Object disregarded, segments not long enough"
else:
best_guess = single_object_classifier(image, range_segments)
if WRITE_TO_FILE:
f.write("Image: %s | Classification: %s\n" % (image, best_guess))
print "\n"
if SINGLE_VALIDATION:
if best_guess.lower() in image.lower():
number_correct += 1
if SINGLE_VALIDATION:
print "\n--------------------------------------------- RESULTS"
result_string = "Correctly identified %s/%s objects." % (number_correct, len(images))
if WRITE_TO_FILE:
f.write(result_string)
f.close()
print result_string
import numpy as np
import os, sys
import classifier as cf
IGM_DIR = "./images/"
NN = False
# モデルをロード
if (len(sys.argv) > 1):
if (sys.argv[1] == "CNN"):
NN = True
print("NN") if NN == False else print("CNN")
cf.load_model(NN)
for dir_name in os.listdir(IGM_DIR):
dir_size = 0
ans_list = np.zeros(10)
print("DIR:", dir_name, end="")
for filename in os.listdir(IGM_DIR + dir_name):
x = cf.load_image(IGM_DIR + dir_name + "/" + filename, NN)
ans = cf.classifier(x)
ans_list[ans] += 1
dir_size += 1
maxIndex = [i for i, x in enumerate(ans_list) if x == max(ans_list)]
print("-> Most:", maxIndex)
print("{0}:".format(dir_size), ans_list)