示例#1
0
def mainLoop():
    n_iter = 0
    last_save = 0
    min_test_MSE = 1.0
    max_iters_after_save = 50

    try:
        while True:
            n_iter += 1
            print "Iteration: %5d " % (n_iter),
            seg_copy = map(lambda (c, seg): (c, cv.CloneImage(seg)), segments)
            seg_copy = map(lambda (c, seg): (c, spoil(seg)), seg_copy)
            shuffle(seg_copy)

            f = open(train_file, "w")
            f.write("%d %d %d\n" % (len(segments), num_input, num_output))

            for c, image in seg_copy:
                image = adjustSize(image, (segW, segH))
                for y in range(image.height):
                    for x in range(image.width):
                        n = image[y, x] / 159.375 - 0.8
                        f.write("%f " % n)
                f.write("\n")
                n = charset.index(c)
                f.write("-1 " * n + "1" + " -1" * (num_output - n - 1) + "\n")

            f.close()

            train = libfann.training_data()
            train.read_train_from_file(train_file)
            ann.train_epoch(train)
            train.destroy_train()
            print "Train MSE: %f " % (ann.get_MSE()),
            print "Train bit fail: %5d " % (ann.get_bit_fail()),
            ann.test_data(test)
            mse = ann.get_MSE()
            print "Test MSE: %f " % (mse),
            print "Test bit fail: %5d " % (ann.get_bit_fail()),
            if mse < min_test_MSE:
                min_test_MSE = mse
                ann.save(ann_file)
                last_save = n_iter
                print "saved",
            if n_iter - last_save > max_iters_after_save: break
            print
    except KeyboardInterrupt:
        print "Interrupted by user."
示例#2
0
文件: train.py 项目: woto/EPC
def mainLoop():
    n_iter = 0
    last_save = 0
    min_test_MSE = 1.0
    max_iters_after_save = 50
    
    try:
        while True:
            n_iter += 1
            print "Iteration: %5d " % (n_iter),
            seg_copy = map(lambda (c, seg): (c, cv.CloneImage(seg)), segments)
            seg_copy = map(lambda (c, seg): (c, spoil(seg)), seg_copy)
            shuffle(seg_copy)
            
            f = open(train_file, "w")
            f.write("%d %d %d\n" % (len(segments), num_input, num_output))
        
            for c, image in seg_copy:
                image = adjustSize(image, (segW, segH))
                for y in range(image.height):
                    for x in range(image.width):
                        n = image[y, x] / 159.375 - 0.8
                        f.write("%f " % n)
                f.write("\n")
                n = charset.index(c)
                f.write("-1 " * n + "1" + " -1" * (num_output - n - 1) + "\n")
        
            f.close()
            
            train = libfann.training_data()
            train.read_train_from_file(train_file)
            ann.train_epoch(train)
            train.destroy_train()
            print "Train MSE: %f " % (ann.get_MSE()),
            print "Train bit fail: %5d " % (ann.get_bit_fail()),
            ann.test_data(test)
            mse = ann.get_MSE()
            print "Test MSE: %f " % (mse),
            print "Test bit fail: %5d " % (ann.get_bit_fail()),
            if mse < min_test_MSE:
                min_test_MSE = mse
                ann.save(ann_file)
                last_save = n_iter
                print "saved",
            if n_iter - last_save > max_iters_after_save: break
            print
    except KeyboardInterrupt: print "Interrupted by user."
示例#3
0
文件: train.py 项目: woto/EPC
segments = os.listdir(segment_dir)

f = open(train_file, "w")
f.write("%d %d %d\n" % (len(segments), num_input, num_output))


for name in segments:
    image = cv.LoadImage(os.path.join(segment_dir, name), cv.CV_LOAD_IMAGE_GRAYSCALE)
    image = adjustSize(image, (segW, segH))
    for y in range(image.height):
        for x in range(image.width):
            n = image[y, x] / 159.375 - 0.8
            f.write("%f " % n)
    f.write("\n")
    c = os.path.splitext(name)[0][0]
    n = charset.index(c)
    f.write("-1 " * n + "1" + " -1" * (num_output - n - 1) + "\n")

f.close()

print "Samples: %d" % len(segments)
print "Input: %d" % num_input
print "Output: %d" % num_output

connection_rate = 1.0
learning_rate = 0.3
num_neurons_hidden = num_input / 3

desired_error = 0.00001
max_iterations = 10000
iterations_between_reports = 20
示例#4
0
segments = os.listdir(segment_dir)

f = open(train_file, "w")
f.write("%d %d %d\n" % (len(segments), num_input, num_output))

for name in segments:
    image = cv.LoadImage(os.path.join(segment_dir, name),
                         cv.CV_LOAD_IMAGE_GRAYSCALE)
    image = adjustSize(image, (segW, segH))
    for y in range(image.height):
        for x in range(image.width):
            n = image[y, x] / 159.375 - 0.8
            f.write("%f " % n)
    f.write("\n")
    c = os.path.splitext(name)[0][0]
    n = charset.index(c)
    f.write("-1 " * n + "1" + " -1" * (num_output - n - 1) + "\n")

f.close()

print "Samples: %d" % len(segments)
print "Input: %d" % num_input
print "Output: %d" % num_output

connection_rate = 1.0
learning_rate = 0.3
num_neurons_hidden = num_input / 3

desired_error = 0.00001
max_iterations = 10000
iterations_between_reports = 20