def setUp(self):
if torch.cuda.is_available():
print('Running tests with CUDA')
sl.init_cuda(0)
else:
print('Running tests without CUDA')
sl.init()
def __init__(self, *args, **kwargs):
super(TestGradients, self).__init__(*args, **kwargs)
sl.init()
self.scene = sl.Scene((640, 480))
# Taken from first YCB frame
# NOTE: This is not constant throughout the real dataset!
fx, fy, cx, cy = 1066.778, 1067.487, 312.9869, 241.3109
self.scene.set_camera_intrinsics(fx, fy, cx, cy)
mesh_files = [os.path.join(TESTS_PATH, 'stanford_bunny', 'scene.gltf')]
self.meshes = []
for mesh_file in mesh_files:
mesh = sl.Mesh(mesh_file)
print("Loaded mesh with bounding box:", mesh.bbox)
print("center:", mesh.bbox.center, "size:", mesh.bbox.size)
mesh.center_bbox()
mesh.scale_to_bbox_diagonal(0.5, 'order_of_magnitude')
print("normalized:", mesh.bbox)
print("center:", mesh.bbox.center, "size:", mesh.bbox.size,
"diagonal:", mesh.bbox.diagonal)
self.meshes.append(mesh)
def run(ycb_path, ibl_path, plane_texture_path):
mesh_path = pathlib.Path(ycb_path) / 'models'
if ibl_path:
ibl_path = pathlib.Path(ibl_path)
sl.init() # use sl.init_cuda() for CUDA interop
# Load all meshes
meshes = sl.Mesh.load_threaded(
[mesh_path / c / 'textured.obj' for c in CLASSES[1:]])
# Setup class IDs
for i, mesh in enumerate(meshes):
mesh.class_index = i + 1
# Create a scene with matching intrinsics
scene = sl.Scene(RESOLUTION)
scene.set_camera_intrinsics(*INTRINSICS)
for mesh in random.sample(meshes, 10):
obj = sl.Object(mesh)
# Override the metallic/roughness parameters so that it gets interesting
obj.metallic = random.random()
obj.roughness = random.random()
scene.add_object(obj)
# Let them fall in a heap
scene.simulate_tabletop_scene()
# Setup lighting
if ibl_path:
scene.light_map = sl.LightMap(ibl_path)
else:
scene.choose_random_light_position()
# Display a plane & set background color
scene.background_plane_size = torch.tensor([3.0, 3.0])
scene.background_color = torch.tensor([0.1, 0.1, 0.1, 1.0])
if plane_texture_path:
scene.background_plane_texture = sl.Texture2D(plane_texture_path)
# Display interactive viewer
sl.view(scene)
# Render a frame
renderer = sl.RenderPass()
result = renderer.render(scene)
# Save as JPEG
Image.fromarray(result.rgb()[:, :, :3].cpu().numpy()).save('rgb.jpeg')
url = 'http://www.hdrlabs.com/sibl/archive/downloads/Circus_Backstage.zip'
r = requests.get(url)
z = zipfile.ZipFile(io.BytesIO(r.content))
z.extractall(SL_PATH / 'examples')
print('done.')
if not (SL_PATH / 'examples' / 'Circus_Backstage').exists():
retrieve_ibl()
import stillleben as sl
import torch
import random
from PIL import Image
sl.init() # use sl.init_cuda() for CUDA interop
# Load a mesh (the constructor accepts pathlib paths)
mesh = sl.Mesh(SL_PATH / 'tests' / 'stanford_bunny' / 'scene.gltf')
# Meshes can come in strange dimensions - rescale to something reasonable
mesh.scale_to_bbox_diagonal(0.5)
# Create a scene with a few bunnies
scene = sl.Scene((1920, 1080))
for i in range(20):
obj = sl.Object(mesh)
# Override the metallic/roughness parameters so that it gets interesting
obj.metallic = random.random()
import torch
import torch.nn.functional as F
import stillleben as sl
import argparse
import json
from pathlib import Path
import visdom
from PIL import Image
import numpy as np
vis = visdom.Visdom(env="synpick_vis", port=8097)
vis.close(env="synpick_vis")
sl.init()
obj_list = ['002_master_chef_can',
'003_cracker_box',
'004_sugar_box',
'005_tomato_soup_can',
'006_mustard_bottle',
'007_tuna_fish_can',
'008_pudding_box',
'009_gelatin_box',
'010_potted_meat_can',
'011_banana',
'019_pitcher_base',
'021_bleach_cleanser',
'024_bowl',
'025_mug',
'035_power_drill',
'036_wood_block',