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‎demo.py

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def test_demo():
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import os
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import b3d
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import b3d.bayes3d as bayes3d
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import genjax
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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from b3d import Mesh, Pose
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from genjax import Pytree
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from tqdm import tqdm
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import b3d
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import b3d.bayes3d as bayes3d
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from b3d import Mesh, Pose
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rr.init("demo")
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rr.connect("127.0.0.1:8812")
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‎demos/detector_segmenter.py

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import io
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import os
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import b3d
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import jax
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import jax.numpy as jnp
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import numpy
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)
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from transformers.models.detr.feature_extraction_detr import rgb_to_id
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import b3d
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processor = OwlViTProcessor.from_pretrained("google/owlvit-base-patch32")
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model = OwlViTForObjectDetection.from_pretrained("google/owlvit-base-patch32")
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‎demos/differentiable_renderer/dense_fitting/standalone_nishad_demo.py

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import functools
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import os
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import b3d
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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import b3d
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from b3d import Pose
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rr.init("gradients")

‎demos/differentiable_renderer/gradient_based_pose_estimation.py

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import os
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from functools import partial
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import jax
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import jax.numpy as jnp
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import optax
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import rerun as rr
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from b3d import Mesh, Pose
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from tqdm import tqdm
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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from b3d import Mesh, Pose
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rr.init("gradients")
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rr.connect("127.0.0.1:8812")
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‎demos/differentiable_renderer/gradients_for_mug.py

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import os
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from functools import partial
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import jax
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import jax.numpy as jnp
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import optax
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import rerun as rr
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import trimesh
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from b3d import Pose
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from tqdm import tqdm
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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from b3d import Pose
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rr.init("gradients")
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rr.connect("127.0.0.1:8812")
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‎demos/differentiable_renderer/patch_tracking/demo_utils.py

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import os
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import b3d
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import b3d.utils as utils
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import jax
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import jax.numpy as jnp
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import trimesh
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import b3d
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import b3d.utils as utils
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from b3d import Pose
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### Utils ###

‎demos/differentiable_renderer/patch_tracking/model.py

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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import genjax
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import jax
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import jax.numpy as jnp
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import rerun as rr
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from b3d.modeling_utils import uniform_pose
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import demos.differentiable_renderer.patch_tracking.demo_utils as utils
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from b3d.modeling_utils import uniform_pose
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def normalize(v):

‎demos/differentiable_renderer/patch_tracking/multiple_patch_tracker_2.py

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import b3d
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import b3d.chisight.dense.patch_tracking as tracking
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import numpy as np
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import rerun as rr
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from b3d.chisight.dense.model import rr_log_uniformpose_meshes_to_image_model_trace
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from tqdm import tqdm
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import b3d
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import b3d.chisight.dense.patch_tracking as tracking
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import demos.differentiable_renderer.patch_tracking.demo_utils as du
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from b3d.chisight.dense.model import rr_log_uniformpose_meshes_to_image_model_trace
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rr.init("multiple_patch_tracking_2")
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rr.connect("127.0.0.1:8812")

‎demos/differentiable_renderer/patch_tracking/multiple_patch_tracking.py

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import os
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import b3d
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import genjax
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import jax
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import jax.numpy as jnp
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import numpy as np
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import optax
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import rerun as rr
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import trimesh
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from b3d import Pose
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from tqdm import tqdm
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import b3d
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import demos.differentiable_renderer.patch_tracking.demo_utils as du
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import demos.differentiable_renderer.patch_tracking.model as m
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from b3d import Pose
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rr.init("multiple_patch_tracking")
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rr.connect("127.0.0.1:8812")

‎demos/differentiable_renderer/patch_tracking/single_patch_tracking_adam.py

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### Preliminaries ###
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import genjax
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import jax
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import jax.numpy as jnp
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import optax
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import rerun as rr
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from b3d import Pose
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from tqdm import tqdm
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import demos.differentiable_renderer.patch_tracking.demo_utils as du
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import demos.differentiable_renderer.patch_tracking.model as m
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from b3d import Pose
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rr.init("single_patch_tracking")
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rr.connect("127.0.0.1:8812")

‎demos/differentiable_renderer/patch_tracking/single_patch_tracking_mh.py

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import time
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import b3d
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import genjax
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import jax
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import jax.numpy as jnp
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import rerun as rr
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from b3d import Pose
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from tqdm import tqdm
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import b3d
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import b3d.chisight.dense.differentiable_renderer as r
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import b3d.chisight.dense.likelihoods as l
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import demos.differentiable_renderer.patch_tracking.demo_utils as du
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import demos.differentiable_renderer.patch_tracking.model as m
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from b3d import Pose
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rr.init("single_patch_tracking-mh")
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rr.connect("127.0.0.1:8812")

‎demos/differentiable_renderer/test_barycentric_interp.py

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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import b3d.chisight.dense.likelihoods as likelihoods
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import jax
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import jax.numpy as jnp
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import rerun as rr
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import b3d.chisight.dense.likelihoods as likelihoods
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from b3d import Pose
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# Set up OpenGL renderer

‎demos/differentiable_renderer/test_basic_gd.py

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import time
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import b3d.chisight.dense.likelihoods as likelihoods
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import genjax
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import jax
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import jax.numpy as jnp
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import rerun as rr
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import b3d.chisight.dense.likelihoods as likelihoods
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import demos.differentiable_renderer.utils as utils
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# Set up OpenGL renderer

‎demos/differentiable_renderer/utils.py

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import b3d
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import jax
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import jax.numpy as jnp
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import b3d
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from b3d import Pose
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‎demos/fork_knife_smc_identity_pose.py

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import os
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import b3d
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import genjax
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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import trimesh
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from b3d import Pose
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from tqdm import tqdm
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import b3d
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from b3d import Pose
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### Choose experiment
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INPUT = "fork-visible" # TODO make one dataset with both objects?

‎demos/graphics_edits_demo/demo_visualize.py

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import os
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import pickle
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import b3d
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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import trimesh
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from b3d import Pose
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from tqdm import tqdm
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import b3d
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from b3d import Pose
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rr.init("demo_visualize3")
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rr.connect("127.0.0.1:8812")
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‎demos/graphics_edits_demo/vkm_demo.py

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import os
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import b3d
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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import trimesh
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import b3d
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from b3d import Pose
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rr.init("vkm_demo2")

‎demos/mesh_fitting/demo.py

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import os
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import b3d
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import genjax
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import jax
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import jax.numpy as jnp
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import optax
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import rerun as rr
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from tqdm import tqdm
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import b3d
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import demos.mesh_fitting.model as m
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import demos.mesh_fitting.tessellation as t
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‎demos/mesh_fitting/demo_depth_init.py

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import os
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import b3d
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import genjax
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import jax
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import rerun as rr
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import b3d
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import demos.mesh_fitting.model as m
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import demos.mesh_fitting.utils as u
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‎demos/mesh_fitting/model.py

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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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import genjax
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import jax
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import jax.numpy as jnp
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import rerun as rr
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import b3d
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import b3d.chisight.dense.differentiable_renderer as rendering
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from b3d.modeling_utils import uniform_pose
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‎demos/mesh_fitting/utils.py

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import b3d
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import jax
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import jax.numpy as jnp
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import b3d
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import demos.mesh_fitting.tessellation as t
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‎demos/posterior_datasets/identity_posterior_data_gen.py

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import os
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import b3d
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import jax
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import jax.numpy as jnp
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import numpy as np
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import rerun as rr
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import trimesh
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import b3d
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width = 200
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height = 200
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fx = 300.0

‎demos/posterior_datasets/pose_posterior_data_gen.py

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import os
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import b3d
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import jax
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import jax.numpy as jnp
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import rerun as rr
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import trimesh
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import b3d
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from b3d import Pose
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rr.init("demo")

‎demos/sparse_model/cotracker.py

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import argparse
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import time
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import b3d
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import numpy as np
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import torch
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import b3d
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parser = argparse.ArgumentParser("r3d_to_video_input")
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parser.add_argument("input", help=".r3d File", type=str)
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args = parser.parse_args()

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