def validate_output(self, sess, num_shapes, epochs):
print('===== validation output')
valid_results_folder = 'epoch-%.2f' % epochs
names, images = sess.run([self.names, self.valid_images])
for k in range(len(names)):
shape_name, view_name = names[k].decode('utf8').split('--')
if view_name == '0':
print(shape_name)
name_output = os.path.join(self.config['train_dir'], valid_results_folder, shape_name, ('output--'+view_name+'.png'))
name_gt = os.path.join(self.config['train_dir'], valid_results_folder, shape_name, ('gt--'+view_name+'.png'))
image.write_image(name_output, images[0, k])
image.write_image(name_gt, images[1, k])
name_normal = os.path.join(self.config['train_dir'], valid_results_folder, shape_name, ('normal--'+view_name+'.png'))
name_depth = os.path.join(self.config['train_dir'], valid_results_folder, shape_name, ('depth--'+view_name+'.png'))
name_mask = os.path.join(self.config['train_dir'], valid_results_folder, shape_name, ('mask--'+view_name+'.png'))
image.write_image(name_normal, images[2, k])
image.write_image(name_depth, images[3, k])
image.write_image(name_mask, images[4, k])
# loop over all remaining shapes in the queue...
num_processed_shapes = self.config['batch_size']
while num_processed_shapes < num_shapes:
sess.run(self.names)
num_processed_shapes += self.config['batch_size']
def test(self, sess, num_patterns):
print('Testing...')
self.saver = tf.train.Saver()
ckpt = tf.train.get_checkpoint_state(self.config.train_dir)
if ckpt and ckpt.model_checkpoint_path:
self.saver.restore(sess, ckpt.model_checkpoint_path)
self.step = int(ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1])
else:
print('Cannot find any checkpoint file')
return
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
self.summarizer = tf.summary.FileWriter(self.config.test_dir, sess.graph)
output_features_folder = 'features'
output_visuals_folder = 'visuals'
output_count = 0
finished = False
while not finished:
if self.config.visualize_feature:
names, visuals = sess.run([self.names, self.visual_features])
else:
names, features = sess.run([self.names, self.image_features])
for k in range(len(names)):
image_name = names[k].decode('utf8')
print('Processed %d: %s' % (output_count, image_name))
if self.config.visualize_feature:
# visualize feature maps
visual_path = os.path.join(self.config.test_dir, output_visuals_folder, image_name)
if not os.path.exists(visual_path):
os.makedirs(visual_path)
for j in range(self.config.feature_size):
offset = k*self.config.feature_size+j
visual_name = os.path.join(visual_path, str(j)+'.png')
image.write_image(visual_name, visuals[offset])
else:
# extract element feature
element_feature = data.extract_element_feature(features[k], image_name, self.config.data_dir)
# export results
name_output = os.path.join(self.config.test_dir, output_features_folder, image_name+'.txt')
# data.write_bin_data(name_output, element_feature)
np.savetxt(name_output, element_feature)
# check termination
output_count += 1
if output_count >= num_patterns:
finished = True
break
coord.request_stop()
coord.join(threads)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--xtiles-per-chunk",
type=int,
required=False,
default=256,
help="Number of tiles per chunk in width direction")
parser.add_argument("--ytiles-per-chunk",
type=int,
required=False,
default=256,
help="Number of tiles per chunk in height direction")
parser.add_argument("--heightmap",
type=str,
required=True,
help="Heightmap filename")
parser.add_argument("--scaling",
type=float,
required=False,
default=1.0,
help="Scaling for converting image pixels to tiles")
parser.add_argument("-o",
type=str,
required=False,
default="./World",
help="Directory for root of the world")
parser.add_argument("-i",
"--image",
type=str,
required=False,
help="Generate an image of the tilemap")
args = parser.parse_args()
scaling = args.scaling
img = Image.open(args.heightmap).convert("L")
if scaling != 1.0:
img = img.resize(
(int(img.size[0] * scaling), int(img.size[1] * scaling)),
Image.BILINEAR)
width_tiles, height_tiles = img.size
xtiles_per_chunk = args.xtiles_per_chunk
ytiles_per_chunk = args.ytiles_per_chunk
output_directory = args.o
create_from_heightmap(
output_directory,
np.array(img.getdata()).reshape(width_tiles, height_tiles),
xtiles_per_chunk, ytiles_per_chunk)
if args.image:
image.write_image(
args.image,
image.create_image(
WorldReader(output_directory).get_tiles(
0, 0, width_tiles, height_tiles)))
def main():
# Image
aspect_ratio = 16.0 / 9.0
image_width = 256
image_height = image_width/aspect_ratio
background = Vector3(0, 0, 0)
samples_per_pixel = 20
max_depth = 1
# World
world = HittableList()
# material_ground = Lambertian(Vector3(0.8, 0.8, 0.0))
# material_center = Lambertian(Vector3(0.7, 0.3, 0.3))
# material_left = Metal(Vector3(0.8, 0.8, 0.8))
material_emissive = DiffuseLight(Vector3(1,1,1), Vector3(1,1,1))
# material_right = Metal(Vector3(0.8, 0.6, 0.2))
# world.append(Sphere(Vector3(0, 0, -1), 0.5, material_center))
# world.append(Sphere(Vector3(1, 0.5, -0.5), 1, material_emissive))
# world.append(Sphere(Vector3(-1, 0, -1), 0.5, material_right))
# world.append(Sphere(Vector3(0, -100.5, -1), 100, material_ground))
sphere_count = 35
sphere_dist = 100
for i in range(0, sphere_count):
world.append(Sphere(Vector3(utils.rand_range(-50, 50), utils.rand_range(-40, 40),
sphere_dist),
1,
material_emissive))
# Camera
look_from = Vector3(0, 0, 0)
look_at = Vector3(0, 0, 1)
v_up = Vector3(0, 1, 0)
dist_to_focus = (look_from - look_at).length()
f_stop = 8
aperture = 1/f_stop
cam = Camera(look_from, look_at, v_up, 30.0, aspect_ratio, aperture, dist_to_focus)
# Render
render_data = list()
print("Commencing Rendering.")
start_time = datetime.now()
for j in reversed(range(0, int(image_height))):
print("Scanlines remaining: %s" % j)
for i in range(0, image_width):
pixel_colour = Vector3(0, 0, 0)
for s in range(0, samples_per_pixel):
u = (i + utils.rand()) / (image_width-1)
v = (j + utils.rand()) / (image_height-1)
r = cam.get_ray(u, v, s)
pixel_colour += ray_colour(r, background, world, max_depth)
render_data.append(colour.write_colour(pixel_colour, samples_per_pixel))
print("\nDone.\nTime Spent: %s" % (datetime.now() - start_time))
file = image.write_image(
width=image_width,
height=image_height,
data=render_data
)
return file
def post(self):
id = self.request.get("id")
if id != '':
item_key = db.Key(id)
item = db.get(item_key)
item_parts_to_write = []
user_id = users.get_current_user().user_id()
user = User.get_by_key_name('key:' + user_id)
if (item.parent().user == users.get_current_user()):
item.title = self.request.get("title")
item.price = float(self.request.get("price"))
item.description = self.request.get("description")
item.category = self.request.get("category")
item.tags = self.request.get("tags").lower()
item.location = user.home
item.currency = user.currency
item.timestamp = datetime.datetime.now()
item_parts_to_write.append(item)
category_string = pluralize(clean_word(self.request.get("category").lower()))
if self.request.get("img"):
image = images.Image(self.request.get("img"))
image_post.write_image(item, image, 0, "")
tags = remove_duplicates([clean_word(word) for word in self.request.get("tags").split(',')])
extra_tags = ['']
for tag in tags:
if len(tag.split()) > 1:
tags.extend(tag.split())
extra_tags.extend(tag.split())
if category_string:
tags.append(category_string)
extra_tags.append(category_string)
singulars = get_singulars(tags)
tags += singulars
extra_tags += singulars
title_words = [clean_word(word) for word in item.title.split(' ')]
tags += title_words
extra_tags += title_words
# Delete old item light so that when sorted by __key__ ascending (default)
# Oldest items (about to expire) show first.
#TODO check if touching or re putting is enough?
db.delete(item.itemlight_set[0])
item_light = ItemLight(parent=user, title=item.title, item_key=item.key(), location=user.home, area=user.area, tags=tags, extra_tags=extra_tags)
item_parts_to_write.append(item_light)
db.put(item_parts_to_write)
logging.info('Item was updated: %s, by user: %s' % (item.title, item.parent().user.nickname()))
else:
user_id = users.get_current_user().user_id()
user = User.get_by_key_name('key:' + user_id)
item = Item(parent=user, location=user.home)
item.currency = user.currency
item.title = self.request.get("title")
item.category = self.request.get("category")
item.tags = self.request.get("tags").lower()
item.price = float(self.request.get("price"))
item.description = self.request.get("description")
item_key = item.put()
category_string = pluralize(clean_word(self.request.get("category").lower()))
if self.request.get("img"):
image = images.Image(self.request.get("img"))
image_post.write_image(item, image, 0, "")
tags = remove_duplicates([clean_word(word) for word in self.request.get("tags").split(',')])
extra_tags = ['']
for tag in tags:
if len(tag.split()) > 1:
tags.extend(tag.split())
extra_tags.extend(tag.split())
if category_string:
tags.append(category_string)
extra_tags.append(category_string)
singulars = get_singulars(tags)
tags += singulars
extra_tags += singulars
title_words = [clean_word(word) for word in item.title.split(' ')]
tags += title_words
extra_tags += title_words
item_light = ItemLight(parent=user, title=item.title, item_key=item_key, location=user.home, area=user.area, tags=tags, extra_tags=extra_tags)
item_light.put()
logging.info('Item was created: %s, by user: %s' % (item.title, item.parent().user.nickname()))
self.response.out.write(cgi.escape(MyEncoder.encode(MyEncoder(), item)))
self.response.headers.add_header('Location', '/item/' + str(item.key()))
self.response.set_status(201)
def test(self, sess, views, num_shapes):
print('Testing...')
self.saver = tf.train.Saver()
ckpt = tf.train.get_checkpoint_state(self.config.train_dir)
if ckpt and ckpt.model_checkpoint_path:
self.saver.restore(sess, ckpt.model_checkpoint_path)
try:
self.step = int(
ckpt.model_checkpoint_path.split('/')[-1].split('-')[-1])
except ValueError:
self.step = 0
else:
print('Cannot find any checkpoint file')
return
coord = tf.train.Coordinator()
threads = tf.train.start_queue_runners(sess=sess, coord=coord)
self.summarizer = tf.summary.FileWriter(self.config.test_dir,
sess.graph)
output_count = 0
output_prefix = 'dn14'
output_images_folder = 'images'
output_results_folder = 'results'
log_file_name = os.path.join(self.config.test_dir, 'log.txt')
log_file = open(log_file_name, 'a')
started = False
finished = False
last_shape_name = ''
last_view_name = ''
while not finished:
names, results, errors, images = sess.run(
[self.names, self.results, self.errors, self.pngs])
for k in range(len(names)):
shape_name, view_name = names[k].decode('utf8').split('--')
if last_shape_name == shape_name:
view_name = ('%s' % (int(last_view_name) + 1))
last_shape_name = shape_name
last_view_name = view_name
print('Processed %d: %s--%s %f' %
(output_count, shape_name, view_name, errors[k]))
if view_name == '0' and started:
log_file.write('\n')
started = True
log_file.write('%6f ' % errors[k])
# export images
name_input = os.path.join(self.config.test_dir,
output_images_folder, shape_name,
'input.png')
image.write_image(name_input, images[0, k])
name_gt = os.path.join(
self.config.test_dir, output_images_folder, shape_name,
('gt-' + output_prefix + '--' + view_name + '.png'))
name_output = os.path.join(
self.config.test_dir, output_images_folder, shape_name,
('pred-' + output_prefix + '--' + view_name + '.png'))
image.write_image(name_gt, images[1, k])
image.write_image(name_output, images[2, k])
name_normal = os.path.join(
self.config.test_dir, output_images_folder, shape_name,
('normal-' + output_prefix + '--' + view_name + '.png'))
name_depth = os.path.join(
self.config.test_dir, output_images_folder, shape_name,
('depth-' + output_prefix + '--' + view_name + '.png'))
name_mask = os.path.join(
self.config.test_dir, output_images_folder, shape_name,
('mask-' + output_prefix + '--' + view_name + '.png'))
image.write_image(name_normal, images[3, k])
image.write_image(name_depth, images[4, k])
image.write_image(name_mask, images[5, k])
# export results
name_output = os.path.join(
self.config.test_dir, output_results_folder, shape_name,
(output_prefix + '-' + view_name + '.png'))
image.write_image(name_output, images[2, k])
# check termination
output_count += 1
if output_count >= num_shapes * views.num_views:
finished = True
break
coord.request_stop()
coord.join(threads)