def save(subdir, b, p, dp, faces, gt_mesh, image, duration=5, fps=50):
from scipy.misc import imsave
from util3d.mesh.obj_io import write_obj
imsave(os.path.join(subdir, 'image.png'), image)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(subdir, 'gt_mesh.obj'), v, f)
save_anim(subdir, b, p, dp, faces, duration, fps)
def save(subdir, b, p, dp, faces, gt_mesh, image, duration=5, fps=50):
from scipy.misc import imsave
from util3d.mesh.obj_io import write_obj
imsave(os.path.join(subdir, 'image.png'), image)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(subdir, 'gt_mesh.obj'), v, f)
save_anim(subdir, b, p, dp, faces, duration, fps)
def save():
import tensorflow as tf
from util3d.mesh.obj_io import write_obj
from shapenet.image import with_background
from template_ffd.model import get_builder
builder = get_builder(model_id)
mesh_fn = builder.get_prediction_to_mesh_fn(0.02)
cloud_fn = builder.get_prediction_to_cloud_fn()
graph = tf.Graph()
with graph.as_default():
image = tf.placeholder(shape=(192, 256, 3), dtype=tf.uint8)
std_image = tf.image.per_image_standardization(image)
std_image = tf.expand_dims(std_image, axis=0)
example_id = tf.constant(['blah'], dtype=tf.string)
spec = builder.get_estimator_spec(
dict(example_id=example_id, image=std_image),
None, tf.estimator.ModeKeys.PREDICT)
predictions = spec.predictions
probs_tf = predictions['probs']
dp_tf = predictions['dp']
saver = tf.train.Saver()
with tf.Session(graph=graph) as sess:
saver.restore(sess, tf.train.latest_checkpoint(builder.model_dir))
for fn in fns:
path = os.path.join(folder, fn)
image_data = np.array(imread(path))
if image_data.shape[-1] == 4:
image_data = with_background(image_data, (255, 255, 255))
probs, dp = sess.run(
[probs_tf, dp_tf], feed_dict={image: image_data})
probs = probs[0]
dp = dp[0]
mesh = mesh_fn(probs, dp)
cloud = cloud_fn(probs, dp)['cloud']
v, ov, f = (
mesh[k] for k in('vertices', 'original_vertices', 'faces'))
path = '%s.obj' % path[:-4]
write_obj(path, v, f)
p2 = '%s_template.obj' % path[:-4]
np.save('%s_cloud.npy' % path[:-4], cloud)
write_obj(p2, ov, f)
def export(cat_desc, example_ids, regime='e'):
from scipy.misc import imsave
from util3d.mesh.obj_io import write_obj
import os
all_ds = get_ds(cat_desc, regime)
base = os.path.realpath(os.path.dirname(__file__))
with all_ds:
for example_id in example_ids:
folder = os.path.join(
base, 'big_table_results', cat_desc, example_id)
if not os.path.isdir(folder):
os.makedirs(folder)
image, gt_mesh, cloud, mesh, voxels, template_mesh = \
all_ds[example_id]
imsave(os.path.join(folder, 'image.png'), image)
v, f = (np.array(mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'deformed.obj'), v, f)
v, f = (np.array(template_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'template.obj'), v, f)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'model.obj'), v, f)
np.save(os.path.join(
folder, 'inferred_cloud.npy'), np.array(cloud))
path = os.path.join(folder, 'deformed.binvox')
voxels.save(path)
def export(cat_desc, example_ids, regime='e'):
from scipy.misc import imsave
from util3d.mesh.obj_io import write_obj
import os
all_ds = get_ds(cat_desc, regime)
base = os.path.realpath(os.path.dirname(__file__))
with all_ds:
for example_id in example_ids:
folder = os.path.join(
base, 'big_table_results', cat_desc, example_id)
if not os.path.isdir(folder):
os.makedirs(folder)
image, gt_mesh, cloud, mesh, voxels, template_mesh = \
all_ds[example_id]
imsave(os.path.join(folder, 'image.png'), image)
v, f = (np.array(mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'deformed.obj'), v, f)
v, f = (np.array(template_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'template.obj'), v, f)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(folder, 'model.obj'), v, f)
np.save(os.path.join(
folder, 'inferred_cloud.npy'), np.array(cloud))
path = os.path.join(folder, 'deformed.binvox')
voxels.save(path)
def export(example_id):
import os
from util3d.mesh.obj_io import write_obj
from scipy.misc import imsave
save_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)),
'top_k_results', example_id)
if not os.path.isdir(save_dir):
os.makedirs(save_dir)
with all_ds:
print(example_id)
image, gt_mesh, predictions = all_ds[example_id]
meshes = top_k_mesh_fn(
*(np.array(predictions[k]) for k in ('probs', 'dp')))
for i, mesh in enumerate(meshes):
ov, v, f = (
mesh[k] for k in ('original_vertices', 'vertices', 'faces'))
write_obj(os.path.join(save_dir, 'template%d.obj' % i), ov, f)
write_obj(os.path.join(save_dir, 'deformed%d.obj' % i), v, f)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(save_dir, 'ground_truth.obj'), v, f)
imsave(os.path.join(save_dir, 'image.png'), image)
def export(example_id):
import os
from util3d.mesh.obj_io import write_obj
from scipy.misc import imsave
save_dir = os.path.join(os.path.realpath(os.path.dirname(__file__)),
'top_k_results', example_id)
if not os.path.isdir(save_dir):
os.makedirs(save_dir)
with all_ds:
print(example_id)
image, gt_mesh, predictions = all_ds[example_id]
meshes = top_k_mesh_fn(*(np.array(predictions[k])
for k in ('probs', 'dp')))
for i, mesh in enumerate(meshes):
ov, v, f = (mesh[k]
for k in ('original_vertices', 'vertices', 'faces'))
write_obj(os.path.join(save_dir, 'template%d.obj' % i), ov, f)
write_obj(os.path.join(save_dir, 'deformed%d.obj' % i), v, f)
v, f = (np.array(gt_mesh[k]) for k in ('vertices', 'faces'))
write_obj(os.path.join(save_dir, 'ground_truth.obj'), v, f)
imsave(os.path.join(save_dir, 'image.png'), image)
def get_mesh():
import numpy as np
from modelnet.parsed import get_saved_dataset
dataset = get_saved_dataset('ModelNet40', 'train', 'toilet')
with dataset as ds:
key = tuple(ds.keys())[2]
mesh = ds[key]
vertices, faces = (np.array(mesh[k])
for k in ('vertices', 'faces'))
return vertices, faces
vertices, faces = get_mesh()
v2, f2 = clean(vertices, faces)
write_obj('/tmp/original.obj', vertices, faces)
write_obj('/tmp/cleaned.obj', v2, f2)
print(vertices.shape)
print(faces.shape)
print(v2.shape)
print(f2.shape)
# def vis(v0, f0, v1, f1):
# from mayavi import mlab
# from util3d.mayavi_vis import vis_mesh
# mlab.figure()
# vis_mesh(v0, f0, color=(0, 0, 1))
# mlab.figure()
# vis_mesh(v1, f1, color=(0, 1, 0))
# mlab.show()
#