コード例 #1
0
ファイル: trainer.py プロジェクト: chyt/CS343-Hw5
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
コード例 #2
0
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)