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Experimental: Add initial wavefront/obj parser for vertices
This PR is an early experimental implementation of wavefront obj parser in tensorflow-io for 3D objects. This PR is the first step to obtain raw vertices in float32 tensor with shape of `[n, 3]`. Additional follow up PRs will be needed to handle meshs with different shapes (not sure if ragged tensor will be a good fit in that case) Signed-off-by: Yong Tang <[email protected]>
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‎WORKSPACE‎

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@@ -1110,3 +1110,14 @@ http_archive(
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"https://github.com/mongodb/mongo-c-driver/releases/download/1.16.2/mongo-c-driver-1.16.2.tar.gz",
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],
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)
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http_archive(
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name = "tinyobjloader",
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build_file = "//third_party:tinyobjloader.BUILD",
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sha256 = "b8c972dfbbcef33d55554e7c9031abe7040795b67778ad3660a50afa7df6ec56",
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strip_prefix = "tinyobjloader-2.0.0rc8",
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urls = [
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"https://storage.googleapis.com/mirror.tensorflow.org/github.com/tinyobjloader/tinyobjloader/archive/v2.0.0rc8.tar.gz",
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"https://github.com/tinyobjloader/tinyobjloader/archive/v2.0.0rc8.tar.gz",
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],
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)

‎tensorflow_io/core/BUILD‎

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@@ -695,6 +695,22 @@ cc_library(
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alwayslink = 1,
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)
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cc_library(
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name = "obj_ops",
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srcs = [
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"kernels/obj_kernels.cc",
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"ops/obj_ops.cc",
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],
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copts = tf_io_copts(),
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linkstatic = True,
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deps = [
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"@local_config_tf//:libtensorflow_framework",
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"@local_config_tf//:tf_header_lib",
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"@tinyobjloader",
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],
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alwayslink = 1,
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)
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cc_binary(
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name = "python/ops/libtensorflow_io.so",
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copts = tf_io_copts(),
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"//tensorflow_io/core:parquet_ops",
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"//tensorflow_io/core:pcap_ops",
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"//tensorflow_io/core:pulsar_ops",
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"//tensorflow_io/core:obj_ops",
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"//tensorflow_io/core:operation_ops",
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"//tensorflow_io/core:pubsub_ops",
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"//tensorflow_io/core:serialization_ops",

‎tensorflow_io/core/kernels/obj_kernels.cc‎

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/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/core/framework/op_kernel.h"
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#include "tensorflow/core/platform/logging.h"
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#include "tiny_obj_loader.h"
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namespace tensorflow {
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namespace io {
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namespace {
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class DecodeObjVertexOp : public OpKernel {
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public:
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explicit DecodeObjVertexOp(OpKernelConstruction* context)
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: OpKernel(context) {}
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void Compute(OpKernelContext* context) override {
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const Tensor* input_tensor;
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OP_REQUIRES_OK(context, context->input("input", &input_tensor));
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OP_REQUIRES(context, TensorShapeUtils::IsScalar(input_tensor->shape()),
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errors::InvalidArgument("input must be scalar, got shape ",
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input_tensor->shape().DebugString()));
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const tstring& input = input_tensor->scalar<tstring>()();
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tinyobj::ObjReader reader;
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if (!reader.ParseFromString(input.c_str(), "")) {
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OP_REQUIRES(
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context, false,
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errors::Internal("Unable to read obj file: ", reader.Error()));
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}
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if (!reader.Warning().empty()) {
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LOG(WARNING) << "TinyObjReader: " << reader.Warning();
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}
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auto& attrib = reader.GetAttrib();
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int64 count = attrib.vertices.size() / 3;
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Tensor* output_tensor = nullptr;
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OP_REQUIRES_OK(context, context->allocate_output(0, TensorShape({count, 3}),
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&output_tensor));
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// Loop over attrib.vertices:
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for (int64 i = 0; i < count; i++) {
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tinyobj::real_t x = attrib.vertices[i * 3 + 0];
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tinyobj::real_t y = attrib.vertices[i * 3 + 1];
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tinyobj::real_t z = attrib.vertices[i * 3 + 2];
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output_tensor->tensor<float, 2>()(i, 0) = x;
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output_tensor->tensor<float, 2>()(i, 1) = y;
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output_tensor->tensor<float, 2>()(i, 2) = z;
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}
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}
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};
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REGISTER_KERNEL_BUILDER(Name("IO>DecodeObjVertex").Device(DEVICE_CPU),
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DecodeObjVertexOp);
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} // namespace
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} // namespace io
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} // namespace tensorflow

‎tensorflow_io/core/ops/obj_ops.cc‎

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/* Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License.
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==============================================================================*/
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#include "tensorflow/core/framework/common_shape_fns.h"
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#include "tensorflow/core/framework/op.h"
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#include "tensorflow/core/framework/shape_inference.h"
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namespace tensorflow {
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namespace io {
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namespace {
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REGISTER_OP("IO>DecodeObjVertex")
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.Input("input: string")
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.Output("output: float32")
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.SetShapeFn([](shape_inference::InferenceContext* c) {
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shape_inference::ShapeHandle unused;
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TF_RETURN_IF_ERROR(c->WithRank(c->input(0), 0, &unused));
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c->set_output(0, c->MakeShape({c->UnknownDim(), 3}));
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return Status::OK();
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});
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} // namespace
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} // namespace io
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} // namespace tensorflow

‎tensorflow_io/core/python/api/experimental/image.py‎

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decode_yuy2,
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decode_avif,
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decode_jp2,
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decode_obj_vertex,
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)

‎tensorflow_io/core/python/experimental/image_ops.py‎

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A `Tensor` of type `uint8` and shape of `[height, width, 3]` (RGB).
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"""
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return core_ops.io_decode_jpeg2k(contents, dtype=dtype, name=name)
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def decode_obj_vertex(contents, name=None):
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"""
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Decode a Wavefront (obj) file into a float32 tensor.
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Args:
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contents: A `Tensor` of type `string`. 0-D. The Wavefront (obj) file.
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name: A name for the operation (optional).
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Returns:
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A `Tensor` of type `float32` and shape of `[n, 3]` for vertices.
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"""
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return core_ops.io_decode_obj_vertex(contents, name=name)

‎tests/test_obj.py‎

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# Copyright 2021 The TensorFlow Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may not
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# use this file except in compliance with the License. You may obtain a copy of
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# the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations under
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# the License.
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# ==============================================================================
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"""Test Wavefront OBJ"""
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import os
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import numpy as np
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import pytest
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import tensorflow as tf
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import tensorflow_io as tfio
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def test_decode_obj_vertices():
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"""Test case for decode obj"""
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filename = os.path.join(
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os.path.dirname(os.path.abspath(__file__)), "test_obj", "sample.obj",
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)
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filename = "file://" + filename
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obj = tfio.experimental.image.decode_obj_vertex(tf.io.read_file(filename))
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expected = np.array(
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[[-0.5, 0.0, 0.4], [-0.5, 0.0, -0.8], [-0.5, 1.0, -0.8], [-0.5, 1.0, 0.4]],
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dtype=np.float32,
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)
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assert np.array_equal(obj, expected)

‎tests/test_obj/sample.obj‎

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# Simple Wavefront file
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v -0.500000 0.000000 0.400000
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v -0.500000 0.000000 -0.800000
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v -0.500000 1.000000 -0.800000
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v -0.500000 1.000000 0.400000
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f -4 -3 -2 -1

‎third_party/tinyobjloader.BUILD‎

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package(default_visibility = ["//visibility:public"])
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licenses(["notice"]) # MIT license
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cc_library(
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name = "tinyobjloader",
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srcs = [
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"tiny_obj_loader.cc",
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],
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hdrs = [
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"tiny_obj_loader.h",
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],
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copts = [],
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)

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