From eb429f3b9ec54cd3e2aed6c947ebe0c005d056e4 Mon Sep 17 00:00:00 2001 From: Gene Kogan Date: Mon, 22 Oct 2018 19:09:00 -0400 Subject: [PATCH] save samples in config.sample_dir --- utils.py | 15 ++++++++------- 1 file changed, 8 insertions(+), 7 deletions(-) diff --git a/utils.py b/utils.py index cd52cb5ec..76b57b6b2 100644 --- a/utils.py +++ b/utils.py @@ -170,11 +170,12 @@ def make_frame(t): clip.write_gif(fname, fps = len(images) / duration) def visualize(sess, dcgan, config, option): + sample_dir = config.sample_dir image_frame_dim = int(math.ceil(config.batch_size**.5)) if option == 0: z_sample = np.random.uniform(-0.5, 0.5, size=(config.batch_size, dcgan.z_dim)) samples = sess.run(dcgan.sampler, feed_dict={dcgan.z: z_sample}) - save_images(samples, [image_frame_dim, image_frame_dim], './samples/test_%s.png' % strftime("%Y-%m-%d-%H-%M-%S", gmtime())) + save_images(samples, [image_frame_dim, image_frame_dim], '%s/test_%s.png' % (sample_dir, strftime("%Y-%m-%d-%H-%M-%S", gmtime()))) elif option == 1: values = np.arange(0, 1, 1./config.batch_size) for idx in xrange(dcgan.z_dim): @@ -192,7 +193,7 @@ def visualize(sess, dcgan, config, option): else: samples = sess.run(dcgan.sampler, feed_dict={dcgan.z: z_sample}) - save_images(samples, [image_frame_dim, image_frame_dim], './samples/test_arange_%s.png' % (idx)) + save_images(samples, [image_frame_dim, image_frame_dim], '%s/test_arange_%s.png' % (sample_dir, idx)) elif option == 2: values = np.arange(0, 1, 1./config.batch_size) for idx in [random.randint(0, dcgan.z_dim - 1) for _ in xrange(dcgan.z_dim)]: @@ -213,9 +214,9 @@ def visualize(sess, dcgan, config, option): samples = sess.run(dcgan.sampler, feed_dict={dcgan.z: z_sample}) try: - make_gif(samples, './samples/test_gif_%s.gif' % (idx)) + make_gif(samples, '%s/test_gif_%s.gif' % (sample_dir, idx)) except: - save_images(samples, [image_frame_dim, image_frame_dim], './samples/test_%s.png' % strftime("%Y-%m-%d-%H-%M-%S", gmtime())) + save_images(samples, [image_frame_dim, image_frame_dim], '%s/test_%s.png' % (sample_dir, strftime("%Y-%m-%d-%H-%M-%S", gmtime()))) elif option == 3: values = np.arange(0, 1, 1./config.batch_size) for idx in xrange(dcgan.z_dim): @@ -225,7 +226,7 @@ def visualize(sess, dcgan, config, option): z[idx] = values[kdx] samples = sess.run(dcgan.sampler, feed_dict={dcgan.z: z_sample}) - make_gif(samples, './samples/test_gif_%s.gif' % (idx)) + make_gif(samples, '%s/test_gif_%s.gif' % (sample_dir, idx)) elif option == 4: image_set = [] values = np.arange(0, 1, 1./config.batch_size) @@ -236,11 +237,11 @@ def visualize(sess, dcgan, config, option): for kdx, z in enumerate(z_sample): z[idx] = values[kdx] image_set.append(sess.run(dcgan.sampler, feed_dict={dcgan.z: z_sample})) - make_gif(image_set[-1], './samples/test_gif_%s.gif' % (idx)) + make_gif(image_set[-1], '%s/test_gif_%s.gif' % (sample_dir, idx)) new_image_set = [merge(np.array([images[idx] for images in image_set]), [10, 10]) \ for idx in range(64) + range(63, -1, -1)] - make_gif(new_image_set, './samples/test_gif_merged.gif', duration=8) + make_gif(new_image_set, '%s/test_gif_merged.gif' % sample_dir , duration=8) def image_manifold_size(num_images):