diff --git a/.gitignore b/.gitignore index 18e6a20..bab79e8 100644 --- a/.gitignore +++ b/.gitignore @@ -8,3 +8,11 @@ code/python/tools/libvrayopenimageio.dylib code/python/tools/libvrayosl.dylib code/python/tools/libVRaySDKLibrary.dylib code/python/tools/plugins +contrib/mikeroberts3000/jupyter/.ipynb_checkpoints +contrib/mikeroberts3000/jupyter/_tmp +contrib/mikeroberts3000/python/libcgauth.dylib +contrib/mikeroberts3000/python/libvray.dylib +contrib/mikeroberts3000/python/libvrayopenimageio.dylib +contrib/mikeroberts3000/python/libvrayosl.dylib +contrib/mikeroberts3000/python/libVRaySDKLibrary.dylib +contrib/mikeroberts3000/python/plugins diff --git a/code/python/lib/embree_utils.py b/code/python/lib/embree_utils.py index 52f39ef..f361454 100644 --- a/code/python/lib/embree_utils.py +++ b/code/python/lib/embree_utils.py @@ -29,11 +29,11 @@ def generate_ray_intersections(vertices, faces, ray_positions, ray_directions, t with h5py.File(tmp_ray_positions_hdf5_file, "w") as f: f.create_dataset("dataset", data=ray_positions) with h5py.File(tmp_ray_directions_hdf5_file, "w") as f: f.create_dataset("dataset", data=ray_directions) - current_source_path = path_utils.get_current_source_file_path(frame=inspect.currentframe()) - generate_octomap_bin = os.path.abspath(os.path.join(current_source_path, "..", "..", "cpp", "bin", "generate_ray_intersections")) + current_source_path = path_utils.get_current_source_file_path(frame=inspect.currentframe()) + generate_ray_intersections_bin = os.path.abspath(os.path.join(current_source_path, "..", "..", "cpp", "bin", "generate_ray_intersections")) cmd = \ - generate_octomap_bin + \ + generate_ray_intersections_bin + \ " --vertices_file=" + tmp_vertices_hdf5_file + \ " --faces_file=" + tmp_faces_hdf5_file + \ " --ray_positions_file=" + tmp_ray_positions_hdf5_file + \ diff --git a/code/python/tools/scene_generate_images_bounding_box.py b/code/python/tools/scene_generate_images_bounding_box.py index 6661a18..d2f373a 100644 --- a/code/python/tools/scene_generate_images_bounding_box.py +++ b/code/python/tools/scene_generate_images_bounding_box.py @@ -132,8 +132,8 @@ far = 1000.0 # construct projection matrix - f_h = tan(fov_y/2.0)*near; - f_w = f_h*width_pixels/height_pixels; + f_h = tan(fov_y/2.0)*near + f_w = f_h*width_pixels/height_pixels left = -f_w right = f_w bottom = -f_h diff --git a/contrib/99991/download.py b/contrib/99991/download.py index 2d525c6..5ccd8cc 100755 --- a/contrib/99991/download.py +++ b/contrib/99991/download.py @@ -544,37 +544,40 @@ def download_files(args): # For each zip file for url in URLS: - f = WebFile(url, session) - z = zipfile.ZipFile(f) + if args.scene is None or args.scene in url: - # for each file in zip file - for entry in z.infolist(): + f = WebFile(url, session) - # skip directories in zip file (will be created automatically) - if entry.is_dir(): - continue + z = zipfile.ZipFile(f) - path = os.path.join(args.directory, entry.filename) + # for each file in zip file + for entry in z.infolist(): - contains_all_words = all( - word in entry.filename for words in args.contains for word in words - ) + # skip directories in zip file (will be created automatically) + if entry.is_dir(): + continue - if args.list: - if contains_all_words: - print(entry.filename) - else: - if contains_all_words: - if os.path.isfile(path) and not args.overwrite: - print("File already exists:", path) - else: - print("Downloading:", path) + path = os.path.join(args.directory, entry.filename) + + contains_all_words = all( + word in entry.filename for words in args.contains for word in words + ) - z.extract(entry.filename, args.directory) + if args.list: + if contains_all_words: + print(entry.filename) else: - if not args.silent: - print("Skipping:", path) + if contains_all_words: + if os.path.isfile(path) and not args.overwrite: + print("File already exists:", path) + else: + print("Downloading:", path) + + z.extract(entry.filename, args.directory) + else: + if not args.silent: + print("Skipping:", path) def main(): @@ -604,6 +607,7 @@ def main(): parser.add_argument("-d", "--directory", type=str, default="downloads", help="directory to download to") parser.add_argument("-o", "--overwrite", action="store_true", help="overwrite existing files") parser.add_argument("-c", "--contains", nargs="*", action="append", default=[], help="only download file if name contains specific word(s)") + parser.add_argument("-e", "--scene", type=str, help="only download files from this scene") parser.add_argument("-s", "--silent", action="store_true", help="only print downloaded files") parser.add_argument("-l", "--list", action="store_true", help="only list files, do not download") diff --git a/contrib/mikeroberts3000/README.md b/contrib/mikeroberts3000/README.md new file mode 100644 index 0000000..d22922f --- /dev/null +++ b/contrib/mikeroberts3000/README.md @@ -0,0 +1,98 @@ +# Working with per-scene camera intrinsics in Hypersim + +Each Hypersim scene uses slightly different camera intrinsics for rendering. This issue arises because some scenes make use of non-standard tilt-shift photography parameters in their scene definition files. This directory provides: (1) a modified perspective projection matrix for each scene that can be used as a drop-in replacement for the usual OpenGL perspective projection matrix; (2) example code demonstrating how the modified projection matrix can be used in applications; and (3) code for computing the modified projection matrix for each scene. + +## Obtaining the perspective projection matrix for a given scene + +The [`metadata_camera_parameters.csv`](metadata_camera_parameters.csv) file contains every camera parameter for every scene obtained directly from the corresponding vrscene file. Each row in this CSV file describes a scene, and the `M_proj_00`, `M_proj_01`, ..., `M_proj_44` columns define the entries of the 4x4 perspective projection matrix for that scene, assuming that camera-space points are stored as [x,y,z,w] column-vectors. For many scenes, this matrix will be the usual OpenGL perspective projection matrix. For other scenes with non-standard tilt-shift parameters, this matrix will be modified to account for the non-standard parameters. + +This [example code](jupyter/00_00_projecting_points_into_hypersim_images.ipynb) demonstrates how to use the projection matrix. + +First, list all files with the command: + +``` +./download.py --list +``` + +Output: + +``` +ai_001_001/_detail/cam_00/camera_keyframe_frame_indices.hdf5 +ai_001_001/_detail/cam_00/camera_keyframe_look_at_positions.hdf5 +ai_001_001/_detail/cam_00/camera_keyframe_orientations.hdf5 +ai_001_001/_detail/cam_00/camera_keyframe_positions.hdf5 +ai_001_001/_detail/cam_00/metadata_camera.csv +ai_001_001/_detail/metadata_cameras.csv +ai_001_001/_detail/metadata_node_strings.csv +ai_001_001/_detail/metadata_nodes.csv +ai_001_001/_detail/metadata_scene.csv +ai_001_001/images/scene_cam_00_final_hdf5/frame.0000.color.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0000.diffuse_illumination.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0000.diffuse_reflectance.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0000.residual.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0001.color.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0001.diffuse_illumination.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0001.diffuse_reflectance.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0001.residual.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0002.color.hdf5 +ai_001_001/images/scene_cam_00_final_hdf5/frame.0002.diffuse_illumination.hdf5 +... +ai_001_001/images/scene_cam_00_final_preview/frame.0000.color.jpg +ai_001_001/images/scene_cam_00_final_preview/frame.0000.diff.jpg +... +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.depth_meters.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.normal_bump_cam.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.normal_bump_world.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.normal_cam.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.normal_world.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.position.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.render_entity_id.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.semantic.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.semantic_instance.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0000.tex_coord.hdf5 +ai_001_002/images/scene_cam_03_geometry_hdf5/frame.0001.depth_meters.hdf5 +... +ai_001_002/images/scene_cam_03_geometry_preview/frame.0000.color.jpg +... +``` + +Next, specify which files you are interested in and download them. +For example, the following command will download the first preview image of each scene: + +``` +./download.py --contains scene_cam_00_final_preview --contains frame.0000.color.jpg --silent +``` + +# Help + + +``` +usage: download.py [-h] [-d DIRECTORY] [-o] [-c [CONTAINS [CONTAINS ...]]] + [-s] [-l] + +optional arguments: + -h, --help show this help message and exit + -d DIRECTORY, --directory DIRECTORY + directory to download to + -o, --overwrite overwrite existing files + -c [CONTAINS [CONTAINS ...]], --contains [CONTAINS [CONTAINS ...]] + only download file if name contains specific word(s) + -s, --silent only print downloaded files + -l, --list only list files, do not download + +example: list files without downloading + + ./download.py --list + +example: download the first preview of each scene: + + ./download.py --contains scene_cam_00_final_preview --contains frame.0000.color.jpg --silent + +example: download all files to "all hypersim images" directory + + ./download.py --directory 'all hypersim images' + +example: print help + + ./download.py --help +``` diff --git a/contrib/mikeroberts3000/jupyter/00_projecting_points_into_hypersim_images.ipynb b/contrib/mikeroberts3000/jupyter/00_projecting_points_into_hypersim_images.ipynb new file mode 100644 index 0000000..9ed6b46 --- /dev/null +++ b/contrib/mikeroberts3000/jupyter/00_projecting_points_into_hypersim_images.ipynb @@ -0,0 +1,219 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c3fdfc9e-b461-49cd-ac46-5fb1d42661fe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Populating the interactive namespace from numpy and matplotlib\n" + ] + } + ], + "source": [ + "%pylab inline\n", + "\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9e5f50de-4436-4087-af49-7e76da7119a7", + "metadata": {}, + "outputs": [], + "source": [ + "import h5py\n", + "import inspect\n", + "import os\n", + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a93c13be-8401-4cad-b5fc-ce77025fa844", + "metadata": {}, + "outputs": [], + "source": [ + "metadata_camera_parameters_csv_file = os.path.join(\"..\", \"metadata_camera_parameters.csv\")\n", + "\n", + "#\n", + "# we use ai_037_002 as our test scene because it has an especially unusual\n", + "# projection matrix and makes use of the the following non-standard lens\n", + "# parameters in V-Ray:\n", + "# \n", + "# horizontal_offset = 0.06\n", + "# horizontal_shift = 0.0\n", + "# lens_shift = -0.009\n", + "# vertical_offset = -0.08\n", + "#\n", + "\n", + "scene_name = \"ai_037_002\"\n", + "camera_name = \"cam_00\"\n", + "frame_id = 0\n", + "\n", + "# project all \"sofa\" vertices into our image\n", + "si = 6\n", + "\n", + "camera_dir = os.path.join(scene_name, \"_detail\", camera_name)\n", + "img_dir = os.path.join(scene_name, \"images\")\n", + "\n", + "# we need access to the Hypersim meshes in order to execute parts of this notebook\n", + "mesh_dir = \"/Volumes/lacie/hypersim/evermotion_dataset/scenes/\" + scene_name + \"/_detail/mesh\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "704e445c-0495-4c92-845a-108d8914346f", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# read parameters from csv file\n", + "#\n", + "\n", + "df_camera_parameters = pd.read_csv(metadata_camera_parameters_csv_file, index_col=\"scene_name\")\n", + "\n", + "df_ = df_camera_parameters.loc[scene_name]\n", + "\n", + "width_pixels = int(df_[\"settings_output_img_width\"])\n", + "height_pixels = int(df_[\"settings_output_img_height\"])\n", + "meters_per_asset_unit = df_[\"settings_units_info_meters_scale\"]\n", + "\n", + "M_proj = matrix([[ df_[\"M_proj_00\"], df_[\"M_proj_01\"], df_[\"M_proj_02\"], df_[\"M_proj_03\"] ],\n", + " [ df_[\"M_proj_10\"], df_[\"M_proj_11\"], df_[\"M_proj_12\"], df_[\"M_proj_13\"] ],\n", + " [ df_[\"M_proj_20\"], df_[\"M_proj_21\"], df_[\"M_proj_22\"], df_[\"M_proj_23\"] ],\n", + " [ df_[\"M_proj_30\"], df_[\"M_proj_31\"], df_[\"M_proj_32\"], df_[\"M_proj_33\"] ]])" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "8282bbf9-1371-4e90-a4f2-12b4bdedd858", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# retrieve all vertices belonging to a particular semantic ID\n", + "#\n", + "\n", + "mesh_vertices_hdf5_file = os.path.join(mesh_dir, \"mesh_vertices.hdf5\")\n", + "mesh_faces_vi_hdf5_file = os.path.join(mesh_dir, \"mesh_faces_vi.hdf5\")\n", + "mesh_faces_oi_hdf5_file = os.path.join(mesh_dir, \"mesh_faces_oi.hdf5\")\n", + "mesh_objects_si_hdf5_file = os.path.join(mesh_dir, \"mesh_objects_si.hdf5\")\n", + "\n", + "with h5py.File(mesh_vertices_hdf5_file, \"r\") as f: mesh_vertices = f[\"dataset\"][:]\n", + "with h5py.File(mesh_faces_vi_hdf5_file, \"r\") as f: mesh_faces_vi = f[\"dataset\"][:]\n", + "with h5py.File(mesh_faces_oi_hdf5_file, \"r\") as f: mesh_faces_oi = f[\"dataset\"][:]\n", + "with h5py.File(mesh_objects_si_hdf5_file, \"r\") as f: mesh_objects_si = f[\"dataset\"][:]\n", + "\n", + "fi_si = where(in1d(mesh_faces_oi, where(mesh_objects_si == si)[0]))[0]\n", + "assert fi_si.shape[0] > 0\n", + "\n", + "mesh_faces_vi_si = mesh_faces_vi[fi_si]\n", + "mesh_vertices_si_ = mesh_vertices[mesh_faces_vi_si.ravel()]\n", + "\n", + "mesh_positions_world = mesh_vertices_si_" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2b9c9dc0-23f6-4f11-9f59-af29bf7e4a84", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", + "text/plain": [ + "
" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#\n", + "# verify that we are projecting points to their correct screen-space positions\n", + "#\n", + "\n", + "camera_positions_hdf5_file = os.path.join(camera_dir, \"camera_keyframe_positions.hdf5\")\n", + "camera_orientations_hdf5_file = os.path.join(camera_dir, \"camera_keyframe_orientations.hdf5\")\n", + "\n", + "depth_meters_hdf5_file = os.path.join(img_dir, \"scene_\" + camera_name + \"_geometry_hdf5\", \"frame.%04d.depth_meters.hdf5\" % frame_id)\n", + "\n", + "with h5py.File(camera_positions_hdf5_file, \"r\") as f: camera_positions = f[\"dataset\"][:]\n", + "with h5py.File(camera_orientations_hdf5_file, \"r\") as f: camera_orientations = f[\"dataset\"][:]\n", + "\n", + "with h5py.File(depth_meters_hdf5_file, \"r\") as f: depth_meters = f[\"dataset\"][:].astype(float32)\n", + "\n", + "# matrix to map to integer screen coordinates from normalized device coordinates\n", + "M_screen_from_ndc = matrix([[0.5*(width_pixels-1), 0, 0, 0.5*(width_pixels-1)],\n", + " [0, -0.5*(height_pixels-1), 0, 0.5*(height_pixels-1)],\n", + " [0, 0, 0.5, 0.5],\n", + " [0, 0, 0, 1.0]])\n", + "\n", + "# get position and rotation matrix for Hypersim image\n", + "camera_position_world = camera_positions[frame_id]\n", + "R_world_from_cam = camera_orientations[frame_id]\n", + "\n", + "t_world_from_cam = matrix(camera_position_world).T\n", + "R_cam_from_world = matrix(R_world_from_cam).T\n", + "t_cam_from_world = -R_cam_from_world*t_world_from_cam\n", + "\n", + "M_cam_from_world = matrix(block([[R_cam_from_world, t_cam_from_world],\n", + " [matrix(zeros(3)), 1.0]]))\n", + "\n", + "num_points = mesh_positions_world.shape[0]\n", + "\n", + "P_world = matrix( c_[ mesh_positions_world, ones(num_points) ] ).T\n", + "P_cam = M_cam_from_world*P_world\n", + "P_clip = M_proj*P_cam\n", + "P_ndc = matrix(P_clip.A/P_clip.A[3])\n", + "P_screen = M_screen_from_ndc*P_ndc\n", + "\n", + "figsize(18,18)\n", + "\n", + "subplot(211)\n", + "imshow(depth_meters)\n", + "title(\"Depth image without projected points\")\n", + "\n", + "subplot(212)\n", + "imshow(depth_meters)\n", + "title(\"Depth image with projected points\")\n", + "scatter(P_screen[0].A1, P_screen[1].A1, color=\"red\", s=0.05);\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/contrib/mikeroberts3000/jupyter/01_casting_rays_that_match_hypersim_images.ipynb b/contrib/mikeroberts3000/jupyter/01_casting_rays_that_match_hypersim_images.ipynb new file mode 100644 index 0000000..f34d358 --- /dev/null +++ b/contrib/mikeroberts3000/jupyter/01_casting_rays_that_match_hypersim_images.ipynb @@ -0,0 +1,202 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "c3fdfc9e-b461-49cd-ac46-5fb1d42661fe", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Populating the interactive namespace from numpy and matplotlib\n" + ] + } + ], + "source": [ + "%pylab inline\n", + "\n", + "%load_ext autoreload\n", + "%autoreload 2" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "9e5f50de-4436-4087-af49-7e76da7119a7", + "metadata": {}, + "outputs": [], + "source": [ + "import h5py\n", + "import inspect\n", + "import os\n", + "import pandas as pd\n", + "\n", + "import path_utils\n", + "path_utils.add_path_to_sys_path(\"../../../code/python/lib\", mode=\"relative_to_cwd\", frame=inspect.currentframe())\n", + "import embree_utils" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "a93c13be-8401-4cad-b5fc-ce77025fa844", + "metadata": {}, + "outputs": [], + "source": [ + "metadata_camera_parameters_csv_file = os.path.join(\"..\", \"metadata_camera_parameters.csv\")\n", + "\n", + "#\n", + "# we use ai_037_002 as our test scene because it has an especially unusual\n", + "# projection matrix and makes use of the the following non-standard lens\n", + "# parameters in V-Ray:\n", + "# \n", + "# horizontal_offset = 0.06\n", + "# horizontal_shift = 0.0\n", + "# lens_shift = -0.009\n", + "# vertical_offset = -0.08\n", + "#\n", + "\n", + "scene_name = \"ai_037_002\"\n", + "camera_name = \"cam_00\"\n", + "frame_id = 0\n", + "\n", + "camera_dir = os.path.join(scene_name, \"_detail\", camera_name)\n", + "img_dir = os.path.join(scene_name, \"images\")\n", + "\n", + "# we need access to the Hypersim meshes in order to execute parts of this notebook\n", + "mesh_dir = \"/Volumes/lacie/hypersim/evermotion_dataset/scenes/\" + scene_name + \"/_detail/mesh\"" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "704e445c-0495-4c92-845a-108d8914346f", + "metadata": {}, + "outputs": [], + "source": [ + "#\n", + "# read parameters from csv file\n", + "#\n", + "\n", + "df_camera_parameters = pd.read_csv(metadata_camera_parameters_csv_file, index_col=\"scene_name\")\n", + "\n", + "df_ = df_camera_parameters.loc[scene_name]\n", + "\n", + "width_pixels = int(df_[\"settings_output_img_width\"])\n", + "height_pixels = int(df_[\"settings_output_img_height\"])\n", + "meters_per_asset_unit = df_[\"settings_units_info_meters_scale\"]\n", + "\n", + "M_cam_from_uv = matrix([[ df_[\"M_cam_from_uv_00\"], df_[\"M_cam_from_uv_01\"], df_[\"M_cam_from_uv_02\"] ],\n", + " [ df_[\"M_cam_from_uv_10\"], df_[\"M_cam_from_uv_11\"], df_[\"M_cam_from_uv_12\"] ],\n", + " [ df_[\"M_cam_from_uv_20\"], df_[\"M_cam_from_uv_21\"], df_[\"M_cam_from_uv_22\"] ]])\n" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "12f02da5-9b6b-4946-a4ec-cbde758ce6d4", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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\n", 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" + ] + }, + "metadata": { + "needs_background": "light" + }, + "output_type": "display_data" + } + ], + "source": [ + "#\n", + "# verify that we are generating correct rays by comparing a Hypersim depth image\n", + "# to a depth image we compute ourselves using our own reference raycaster\n", + "#\n", + "\n", + "# load camera trajectory data, mesh data, and a Hypersim depth image\n", + "camera_positions_hdf5_file = os.path.join(camera_dir, \"camera_keyframe_positions.hdf5\")\n", + "camera_orientations_hdf5_file = os.path.join(camera_dir, \"camera_keyframe_orientations.hdf5\")\n", + "\n", + "mesh_vertices_hdf5_file = os.path.join(mesh_dir, \"mesh_vertices.hdf5\")\n", + "mesh_faces_vi_hdf5_file = os.path.join(mesh_dir, \"mesh_faces_vi.hdf5\")\n", + "mesh_faces_oi_hdf5_file = os.path.join(mesh_dir, \"mesh_faces_oi.hdf5\")\n", + "mesh_objects_si_hdf5_file = os.path.join(mesh_dir, \"mesh_objects_si.hdf5\")\n", + "\n", + "depth_meters_hdf5_file = os.path.join(img_dir, \"scene_\" + camera_name + \"_geometry_hdf5\", \"frame.%04d.depth_meters.hdf5\" % frame_id)\n", + "\n", + "with h5py.File(camera_positions_hdf5_file, \"r\") as f: camera_positions = f[\"dataset\"][:]\n", + "with h5py.File(camera_orientations_hdf5_file, \"r\") as f: camera_orientations = f[\"dataset\"][:]\n", + "\n", + "with h5py.File(mesh_vertices_hdf5_file, \"r\") as f: mesh_vertices = f[\"dataset\"][:]\n", + "with h5py.File(mesh_faces_vi_hdf5_file, \"r\") as f: mesh_faces_vi = f[\"dataset\"][:]\n", + "with h5py.File(mesh_faces_oi_hdf5_file, \"r\") as f: mesh_faces_oi = f[\"dataset\"][:]\n", + "with h5py.File(mesh_objects_si_hdf5_file, \"r\") as f: mesh_objects_si = f[\"dataset\"][:]\n", + "\n", + "with h5py.File(depth_meters_hdf5_file, \"r\") as f: hypersim_depth_meters = f[\"dataset\"][:].astype(float32)\n", + "\n", + "# get position and rotation matrix for Hypersim image\n", + "camera_position_world = camera_positions[frame_id]\n", + "R_world_from_cam = camera_orientations[frame_id]\n", + "\n", + "# create grid of uv-values\n", + "u_min = -1.0\n", + "u_max = 1.0\n", + "v_min = -1.0\n", + "v_max = 1.0\n", + "half_du = 0.5 * (u_max - u_min) / width_pixels\n", + "half_dv = 0.5 * (v_max - v_min) / height_pixels\n", + "\n", + "u, v = meshgrid(linspace(u_min+half_du, u_max-half_du, width_pixels),\n", + " linspace(v_min+half_dv, v_max-half_dv, height_pixels)[::-1])\n", + "\n", + "uvs_2d = dstack((u,v,np.ones_like(u)))\n", + "P_uv = matrix(uvs_2d.reshape(-1,3)).T\n", + "\n", + "# compute our own rays\n", + "P_world = R_world_from_cam * M_cam_from_uv * P_uv\n", + "ray_directions_world = P_world.T.A\n", + "ray_positions_world = ones_like(ray_directions_world) * camera_position_world\n", + "\n", + "# get intersection distances using our own reference raycaster,\n", + "# reshape into 2D image, scale to meters\n", + "intersection_distances, intersection_normals, prim_ids = \\\n", + " embree_utils.generate_ray_intersections(mesh_vertices, mesh_faces_vi, ray_positions_world, ray_directions_world, tmp_dir=\"_tmp\")\n", + "\n", + "intersection_distances_2d = intersection_distances.reshape(height_pixels, width_pixels) * meters_per_asset_unit\n", + "difference = hypersim_depth_meters - intersection_distances_2d\n", + "\n", + "figsize(18,27)\n", + "\n", + "subplot(311); imshow(hypersim_depth_meters); title(\"Depth image from the Hypersim Dataset\");\n", + "subplot(312); imshow(intersection_distances_2d); title(\"Depth image from our reference raycaster\");\n", + "subplot(313); imshow(difference); title(\"Difference image\");\n" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.7.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_orientations.hdf5 b/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_orientations.hdf5 new file mode 100644 index 0000000..d2299ce Binary files /dev/null and b/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_orientations.hdf5 differ diff --git a/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_positions.hdf5 b/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_positions.hdf5 new file mode 100644 index 0000000..4aaf93c Binary files /dev/null and b/contrib/mikeroberts3000/jupyter/ai_037_002/_detail/cam_00/camera_keyframe_positions.hdf5 differ diff --git a/contrib/mikeroberts3000/jupyter/ai_037_002/images/scene_cam_00_geometry_hdf5/frame.0000.depth_meters.hdf5 b/contrib/mikeroberts3000/jupyter/ai_037_002/images/scene_cam_00_geometry_hdf5/frame.0000.depth_meters.hdf5 new file mode 100644 index 0000000..201960c Binary files /dev/null and b/contrib/mikeroberts3000/jupyter/ai_037_002/images/scene_cam_00_geometry_hdf5/frame.0000.depth_meters.hdf5 differ diff --git a/contrib/mikeroberts3000/jupyter/path_utils.py b/contrib/mikeroberts3000/jupyter/path_utils.py new file mode 100644 index 0000000..7b12b5f --- /dev/null +++ b/contrib/mikeroberts3000/jupyter/path_utils.py @@ -0,0 +1,23 @@ +# +# For licensing see accompanying LICENSE.txt file. +# Copyright (C) 2020 Apple Inc. All Rights Reserved. +# + +import os, sys, inspect + +def add_path_to_sys_path(path, mode, frame): + assert mode == "unchanged" or mode == "relative_to_cwd" or mode == "relative_to_current_source_dir" + if mode == "unchanged": + if path not in sys.path: + sys.path.insert(0,path) + if mode == "relative_to_cwd": + realpath = os.path.realpath(os.path.abspath(path)) + if realpath not in sys.path: + sys.path.insert(0,realpath) + if mode == "relative_to_current_source_dir": + realpath = os.path.realpath(os.path.abspath(os.path.join(os.path.dirname(inspect.getfile(frame)),path))) + if realpath not in sys.path: + sys.path.insert(0,realpath) + +def get_current_source_file_path(frame): + return os.path.realpath(os.path.abspath(os.path.join(os.path.dirname(inspect.getfile(frame))))) diff --git a/contrib/mikeroberts3000/metadata_camera_parameters.csv b/contrib/mikeroberts3000/metadata_camera_parameters.csv new file mode 100644 index 0000000..7b9839a --- /dev/null +++ b/contrib/mikeroberts3000/metadata_camera_parameters.csv @@ -0,0 +1,483 @@ +scene_name,settings_output_img_height,settings_output_img_width,settings_units_info_meters_scale,use_camera_physical,camera_physical_anisotropy,camera_physical_blades_enable,camera_physical_blades_num,camera_physical_blades_rotation,camera_physical_bmpaperture_affects_exposure,camera_physical_bmpaperture_enable,camera_physical_bmpaperture_resolution,camera_physical_bmpaperture_tex,camera_physical_center_bias,camera_physical_distortion,camera_physical_distortion_tex,camera_physical_distortion_type,camera_physical_dof_display_threshold,camera_physical_dont_affect_settings,camera_physical_enable_thin_lens_equation,camera_physical_exposure,camera_physical_f_number,camera_physical_film_width,camera_physical_focal_length,camera_physical_focus_distance,camera_physical_fov,camera_physical_horizontal_offset,camera_physical_horizontal_shift,camera_physical_ISO,camera_physical_latency,camera_physical_lens_file,camera_physical_lens_shift,camera_physical_optical_vignetting,camera_physical_rolling_shutter_duration,camera_physical_rolling_shutter_mode,camera_physical_shutter_angle,camera_physical_shutter_offset,camera_physical_shutter_speed,camera_physical_specify_focus,camera_physical_specify_fov,camera_physical_subdivs,camera_physical_target_distance,camera_physical_targeted,camera_physical_type,camera_physical_use_dof,camera_physical_use_moblur,camera_physical_vertical_offset,camera_physical_vignetting,camera_physical_white_balance,camera_physical_zoom_factor,settings_camera_auto_corrections_mode,settings_camera_auto_exposure,settings_camera_auto_exposure_compensation,settings_camera_auto_fit,settings_camera_auto_white_balance,settings_camera_curve,settings_camera_dist,settings_camera_dont_affect_settings,settings_camera_fov,settings_camera_height,settings_camera_image_planes,settings_camera_type,M_cam_from_uv_00,M_cam_from_uv_01,M_cam_from_uv_02,M_cam_from_uv_10,M_cam_from_uv_11,M_cam_from_uv_12,M_cam_from_uv_20,M_cam_from_uv_21,M_cam_from_uv_22,M_proj_00,M_proj_01,M_proj_02,M_proj_03,M_proj_10,M_proj_11,M_proj_12,M_proj_13,M_proj_20,M_proj_21,M_proj_22,M_proj_23,M_proj_30,M_proj_31,M_proj_32,M_proj_33 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argparse.ArgumentParser() +parser.add_argument("--dataset_dir", required=True) +parser.add_argument("--out_file", required=True) +parser.add_argument("--scene_names") +args = parser.parse_args() + +assert os.path.exists(args.dataset_dir) + +import path_utils +path_utils.add_path_to_sys_path(args.dataset_dir, mode="relative_to_cwd", frame=inspect.currentframe()) +import _dataset_config + + + +print("[HYPERSIM: DATASET_GENERATE_CAMERA_PARAMETERS_METADATA] Begin...") + + + +df_camera_parameters_columns = [ + "scene_name", + "settings_output_img_height", + "settings_output_img_width", + "settings_units_info_meters_scale", + "use_camera_physical", + "camera_physical_anisotropy", + "camera_physical_blades_enable", + "camera_physical_blades_num", + "camera_physical_blades_rotation", + "camera_physical_bmpaperture_affects_exposure", + "camera_physical_bmpaperture_enable", + "camera_physical_bmpaperture_resolution", + "camera_physical_bmpaperture_tex", + "camera_physical_center_bias", + "camera_physical_distortion", + "camera_physical_distortion_tex", + "camera_physical_distortion_type", + "camera_physical_dof_display_threshold", + "camera_physical_dont_affect_settings", + "camera_physical_enable_thin_lens_equation", + "camera_physical_exposure", + "camera_physical_f_number", + "camera_physical_film_width", + "camera_physical_focal_length", + "camera_physical_focus_distance", + "camera_physical_fov", + "camera_physical_horizontal_offset", + "camera_physical_horizontal_shift", + "camera_physical_ISO", + "camera_physical_latency", + "camera_physical_lens_file", + "camera_physical_lens_shift", + "camera_physical_optical_vignetting", + "camera_physical_rolling_shutter_duration", + "camera_physical_rolling_shutter_mode", + "camera_physical_shutter_angle", + "camera_physical_shutter_offset", + "camera_physical_shutter_speed", + "camera_physical_specify_focus", + "camera_physical_specify_fov", + "camera_physical_subdivs", + "camera_physical_target_distance", + "camera_physical_targeted", + "camera_physical_type", + "camera_physical_use_dof", + "camera_physical_use_moblur", + "camera_physical_vertical_offset", + "camera_physical_vignetting", + "camera_physical_white_balance", + "camera_physical_zoom_factor", + "settings_camera_auto_corrections_mode", + "settings_camera_auto_exposure", + "settings_camera_auto_exposure_compensation", + "settings_camera_auto_fit", + "settings_camera_auto_white_balance", + "settings_camera_curve", + "settings_camera_dist", + "settings_camera_dont_affect_settings", + "settings_camera_fov", + "settings_camera_height", + "settings_camera_image_planes", + "settings_camera_type", + "M_cam_from_uv_00", "M_cam_from_uv_01", "M_cam_from_uv_02", + "M_cam_from_uv_10", "M_cam_from_uv_11", "M_cam_from_uv_12", + "M_cam_from_uv_20", "M_cam_from_uv_21", "M_cam_from_uv_22", + "M_proj_00", "M_proj_01", "M_proj_02", "M_proj_03", + "M_proj_10", "M_proj_11", "M_proj_12", "M_proj_13", + "M_proj_20", "M_proj_21", "M_proj_22", "M_proj_23", + "M_proj_30", "M_proj_31", "M_proj_32", "M_proj_33" ] + +df_camera_parameters = pd.DataFrame(columns=df_camera_parameters_columns) + +if args.scene_names is not None: + scenes = [ s for s in _dataset_config.scenes if fnmatch.fnmatch(s["name"], args.scene_names) ] +else: + scenes = _dataset_config.scenes + + + +for s in scenes: + + # + # We load the vrscene precisely as it has been exported from 3ds Max, + # before it has been modified by the Hypersim pipeline in any way. This + # is done as a matter of convenience, so that this script can be run + # after running the bare minimum part of the Hypersim pipeline. + # + + scene_name = s["name"] + scene_file = os.path.join(args.dataset_dir, "scenes", scene_name, "_asset_export", "scene.vrscene") + vray_user_params_dir = args.dataset_dir + + renderer = vray.VRayRenderer() + def log_msg(renderer, message, level, instant): + print(str(instant) + " " + str(level) + " " + message) + renderer.setOnLogMessage(log_msg) + renderer.load(scene_file) + time.sleep(0.5) + + # + # We must execute the _set_vray_user_params(...) function + # because this user code might modify camera parameters. + # + + path_utils.add_path_to_sys_path(vray_user_params_dir, mode="relative_to_cwd", frame=inspect.currentframe()) + import _vray_user_params + + camera_params = _vray_user_params._set_vray_user_params(renderer) + + + + camera_physicals = renderer.classes.CameraPhysical.getInstances() + settings_camera = renderer.classes.SettingsCamera.getInstances()[0] + settings_output = renderer.classes.SettingsOutput.getInstances()[0] + settings_units_info = renderer.classes.SettingsUnitsInfo.getInstances()[0] + + use_camera_physical = len(camera_physicals) > 0 + + + + # parameters from vrscene file + width_pixels = settings_output.img_width + height_pixels = settings_output.img_height + meters_per_asset_unit = settings_units_info.meters_scale + + + + if use_camera_physical: + + camera_physical = camera_physicals[0] + + # parameters from CameraPhysical + film_width = camera_physical.film_width + focus_distance = camera_physical.focus_distance + fov_x = camera_physical.fov + horizontal_offset = camera_physical.horizontal_offset + horizontal_shift = camera_physical.horizontal_shift + lens_shift = camera_physical.lens_shift + specify_focus = camera_physical.specify_focus + target_distance = camera_physical.target_distance + vertical_offset = camera_physical.vertical_offset + zoom = camera_physical.zoom_factor + + # derived parameters + fov_y = 2.0 * np.arctan(height_pixels * np.tan(fov_x/2.0) / width_pixels) + + if specify_focus: + lens_params_focus_distance = focus_distance + else: + lens_params_focus_distance = target_distance + + lens_params_film_width = film_width*(1.0/meters_per_asset_unit)*0.001 + lens_params_zoom = zoom + + + + # + # Binary search for the aperture distance that matches specified FOV. + # + + # + # In this function, we adopt the convention that the horizontal extent of + # the frustum goes from rx=-0.5 to rx=0.5 to match the V-Ray implementation + # as closely as possible. We could modify this function to match our + # conventions (where the horizontal extent of the the frustum goes from + # u=-1.0 to u=1.0), but there is no need, so we leave this function as-is. + # + + def compute_ray_camera_space(rx, ry, zval): + + rx += horizontal_offset + ry += vertical_offset + + k = -lens_params_focus_distance/zval + px = rx*lens_params_film_width*k/lens_params_zoom + py = ry*lens_params_film_width*k/lens_params_zoom + pz = lens_params_focus_distance + + shiftkx = np.sqrt(1.0 + horizontal_shift**2.0) + shiftk = np.sqrt(1.0 + lens_shift**2.0) + + px_ = px/shiftkx + py_ = py/shiftk + pz_ = pz + ((py_*lens_shift) + (px_*horizontal_shift)) + + r = np.array([px_, py_, -pz_]) + return r + + lens_params_aperture_dist_min = 0.0001 + lens_params_aperture_dist_max = 500.0 + lens_params_aperture_dist_curr = (lens_params_aperture_dist_min+lens_params_aperture_dist_max)/2.0 + + ray_l = compute_ray_camera_space(-0.5, 0.0, lens_params_aperture_dist_curr) + ray_r = compute_ray_camera_space( 0.5, 0.0, lens_params_aperture_dist_curr) + + # This code does not exactly calculate the angle between ray_l + # and ray_r, but it's used by V-Ray to compute aperture distance, + # and we want to match V-Ray's behavior exactly. + + ray_l_ = ray_l / ray_l[2] + ray_r_ = ray_r / ray_r[2] + width = ray_r_[0] - ray_l_[0] + fov_x_aperture_dist_est = np.arctan(0.5*width)*2.0 + + num_steps = 100 + eps = 1e-9 + + for i in range(num_steps): + if abs(fov_x_aperture_dist_est - fov_x) < eps: + break + + if fov_x_aperture_dist_est < fov_x: + lens_params_aperture_dist_max = lens_params_aperture_dist_curr + lens_params_aperture_dist_curr = (lens_params_aperture_dist_min+lens_params_aperture_dist_max)/2.0 + else: + lens_params_aperture_dist_min = lens_params_aperture_dist_curr + lens_params_aperture_dist_curr = (lens_params_aperture_dist_min+lens_params_aperture_dist_max)/2.0 + + ray_l = compute_ray_camera_space(-0.5, 0.0, lens_params_aperture_dist_curr) + ray_r = compute_ray_camera_space( 0.5, 0.0, lens_params_aperture_dist_curr) + + # This code does not exactly calculate the angle between ray_l + # and ray_r, but it's used by V-Ray to compute aperture distance, + # and we want to match V-Ray's behavior exactly. + + ray_l_ = ray_l / ray_l[2] + ray_r_ = ray_r / ray_r[2] + width = ray_r_[0] - ray_l_[0] + fov_x_aperture_dist_est = np.arctan(0.5*width)*2.0 + + lens_params_aperture_dist = lens_params_aperture_dist_curr + + + + # + # Construct matrix to map points to camera-space from uv-space, ignore all camera parameters for now. + # + + M_cam_from_uv_canonical = np.matrix([[np.tan(fov_x/2.0), 0.0, 0.0], + [0.0, np.tan(fov_y/2.0), 0.0], + [0.0, 0.0, -1.0]]) + + eps = 0.0001 + assert abs(np.linalg.det(M_cam_from_uv_canonical)) > eps + + # print(M_cam_from_uv_canonical) + # print() + + + + # + # Construct matrix to map points to camera-space from uv-space, take camera parameters into account here. + # + + zval = lens_params_aperture_dist + k = -lens_params_focus_distance/zval + shiftkx = np.sqrt(1.0 + horizontal_shift**2.0) + shiftk = np.sqrt(1.0 + lens_shift**2.0) + + k_x = lens_params_film_width*k*(1.0/lens_params_zoom)*(1.0/shiftkx) + k_x_u = -0.5*k_x + k_x_v = 0.0 + k_x_c = horizontal_offset*k_x + + k_y = lens_params_film_width*k*(1.0/lens_params_zoom)*(1.0/shiftk) + k_y_u = 0.0 + k_y_v = -0.5*k_y*(height_pixels/width_pixels) + k_y_c = vertical_offset*k_y + + k_z_u = -horizontal_shift*k_x_u + k_z_v = -lens_shift*k_y_v + k_z_c = -lens_params_focus_distance - lens_shift*k_y_c - horizontal_shift*k_x_c + + M_cam_from_uv_transformed = np.matrix([[k_x_u, k_x_v, k_x_c], + [k_y_u, k_y_v, k_y_c], + [k_z_u, k_z_v, k_z_c]]) + + eps = 0.0001 + assert abs(np.linalg.det(M_cam_from_uv_transformed)) > eps + + # print(M_cam_from_uv_transformed) + # print() + + + + # + # The scale of M_cam_from_uv_transformed is arbitrary, but we would prefer to define + # it in a way that is as convenient as possible in OpenGL applications. So we solve + # for the scalar parameter k that minimizes the following expression: + # + # np.linalg.norm(np.identity(3) - M_cam_from_uv_canonical*(k*M_cam_from_uv_transformed).I)**2.0 + # + # By rescaling in this way, we will eventually obtain a modified projection matrix + # that is (roughly speaking) as similar as possible to the usual OpenGL projection + # matrix, so it can be used in OpenGL applications without needing to drastically + # alter the near and far clipping planes. + # + # Note that our strategy is not exactly equivalent to minimizing the difference + # between the usual OpenGL projection matrix and our modified projection matrix. But + # it is more mathematically convenient, and produces very similar results empirically. + # + + # expression we would like to minimize + k = 1.0 + norm_squared = np.linalg.norm(np.identity(3) - M_cam_from_uv_canonical*(k*M_cam_from_uv_transformed).I)**2.0 + # print(norm_squared) + # print() + + # we can express as a scalar quadratic in k_inv + k_inv = 1.0/k + A = np.identity(3) + B = (M_cam_from_uv_canonical*M_cam_from_uv_transformed.I).A + a = np.sum(B*B) + b = -2.0*np.sum(A*B) + c = np.sum(A*A) + norm_squared = a*k_inv**2.0 + b*k_inv + c + # print(norm_squared) + # print() + + # analytic optimal solution for k_inv + k_inv_opt = -b/(2.0*a) + + # analytic optimal solution for k + k_opt = 1.0/k_inv_opt + + # print(k_opt) + # print() + + # optimal norm squared value + norm_squared_opt = np.linalg.norm(np.identity(3) - M_cam_from_uv_canonical*(k_opt*M_cam_from_uv_transformed).I)**2 + + # print(norm_squared_opt) + # print() + + M_cam_from_uv_transformed_scaled = k_opt*M_cam_from_uv_transformed + + # print(M_cam_from_uv_transformed_scaled) + # print() + + M_cam_from_uv_ = M_cam_from_uv_transformed_scaled + + + + # + # Construct a standard OpenGL projection matrix, ignore V-Ray camera parameters for now. + # + + near = 1.0 + far = 1000.0 + + # construct projection matrix + f_h = np.tan(fov_y/2.0)*near + f_w = f_h*width_pixels/height_pixels + left = -f_w + right = f_w + bottom = -f_h + top = f_h + + M_proj = matrix(zeros((4,4))) + M_proj[0,0] = (2.0*near)/(right - left) + M_proj[1,1] = (2.0*near)/(top - bottom) + M_proj[0,2] = (right + left)/(right - left) + M_proj[1,2] = (top + bottom)/(top - bottom) + M_proj[2,2] = -(far + near)/(far - near) + M_proj[3,2] = -1.0 + M_proj[2,3] = -(2.0*far*near)/(far - near) + + # print(M_proj) + # print() + + + + # + # Construct modified projection matrix that takes V-Ray camera parameters into account. + # + + M_canonical_from_transformed = M_cam_from_uv_canonical*(M_cam_from_uv_transformed_scaled).I + M_canonical_from_transformed_ = scipy.linalg.block_diag(M_canonical_from_transformed, 1) + M_proj_transformed = M_proj*M_canonical_from_transformed_ + + # print(M_proj_transformed) + # print() + + M_proj_ = M_proj_transformed + + + + else: + + # parameters from SettingsCamera + fov_x = settings_camera.fov + + # derived parameters + fov_y = 2.0 * np.arctan(height_pixels * np.tan(fov_x/2.0) / width_pixels) + + # + # Construct matrix to map points to camera-space from uv-space, ignore all camera parameters for now. + # + + M_cam_from_uv_canonical = np.matrix([[np.tan(fov_x/2.0), 0.0, 0.0], + [0.0, np.tan(fov_y/2.0), 0.0], + [0.0, 0.0, -1.0]]) + + eps = 0.0001 + assert abs(np.linalg.det(M_cam_from_uv_canonical)) > eps + + # print(M_cam_from_uv_canonical) + # print() + + M_cam_from_uv_ = M_cam_from_uv_canonical + + # + # Construct a standard OpenGL projection matrix. + # + + near = 1.0 + far = 1000.0 + + # construct projection matrix + f_h = np.tan(fov_y/2.0)*near + f_w = f_h*width_pixels/height_pixels + left = -f_w + right = f_w + bottom = -f_h + top = f_h + + M_proj = matrix(zeros((4,4))) + M_proj[0,0] = (2.0*near)/(right - left) + M_proj[1,1] = (2.0*near)/(top - bottom) + M_proj[0,2] = (right + left)/(right - left) + M_proj[1,2] = (top + bottom)/(top - bottom) + M_proj[2,2] = -(far + near)/(far - near) + M_proj[3,2] = -1.0 + M_proj[2,3] = -(2.0*far*near)/(far - near) + + M_proj_ = M_proj + + + + df_camera_parameters_ = pd.DataFrame( + columns=df_camera_parameters_columns, + data={ + "scene_name" : [ scene_name ], + "settings_output_img_height" : [ settings_output.img_height ], + "settings_output_img_width" : [ settings_output.img_width ], + "settings_units_info_meters_scale" : [ settings_units_info.meters_scale ], + "use_camera_physical" : [ use_camera_physical ], + "camera_physical_anisotropy" : [ camera_physical.anisotropy if use_camera_physical else None ], + "camera_physical_blades_enable" : [ camera_physical.blades_enable if use_camera_physical else None ], + "camera_physical_blades_num" : [ camera_physical.blades_num if use_camera_physical else None ], + "camera_physical_blades_rotation" : [ camera_physical.blades_rotation if use_camera_physical else None ], + "camera_physical_bmpaperture_affects_exposure" : [ camera_physical.bmpaperture_affects_exposure if use_camera_physical else None ], + "camera_physical_bmpaperture_enable" : [ camera_physical.bmpaperture_enable if use_camera_physical else None ], + "camera_physical_bmpaperture_resolution" : [ camera_physical.bmpaperture_resolution if use_camera_physical else None ], + "camera_physical_bmpaperture_tex" : [ camera_physical.bmpaperture_tex if use_camera_physical else None ], + "camera_physical_center_bias" : [ camera_physical.center_bias if use_camera_physical else None ], + "camera_physical_distortion" : [ camera_physical.distortion if use_camera_physical else None ], + "camera_physical_distortion_tex" : [ camera_physical.distortion_tex if use_camera_physical else None ], + "camera_physical_distortion_type" : [ camera_physical.distortion_type if use_camera_physical else None ], + "camera_physical_dof_display_threshold" : [ camera_physical.dof_display_threshold if use_camera_physical else None ], + "camera_physical_dont_affect_settings" : [ camera_physical.dont_affect_settings if use_camera_physical else None ], + "camera_physical_enable_thin_lens_equation" : [ camera_physical.enable_thin_lens_equation if use_camera_physical else None ], + "camera_physical_exposure" : [ camera_physical.exposure if use_camera_physical else None ], + "camera_physical_f_number" : [ camera_physical.f_number if use_camera_physical else None ], + "camera_physical_film_width" : [ camera_physical.film_width if use_camera_physical else None ], + "camera_physical_focal_length" : [ camera_physical.focal_length if use_camera_physical else None ], + "camera_physical_focus_distance" : [ camera_physical.focus_distance if use_camera_physical else None ], + "camera_physical_fov" : [ camera_physical.fov if use_camera_physical else None ], + "camera_physical_horizontal_offset" : [ camera_physical.horizontal_offset if use_camera_physical else None ], + "camera_physical_horizontal_shift" : [ camera_physical.horizontal_shift if use_camera_physical else None ], + "camera_physical_ISO" : [ camera_physical.ISO if use_camera_physical else None ], + "camera_physical_latency" : [ camera_physical.latency if use_camera_physical else None ], + "camera_physical_lens_file" : [ camera_physical.lens_file if use_camera_physical else None ], + "camera_physical_lens_shift" : [ camera_physical.lens_shift if use_camera_physical else None ], + "camera_physical_optical_vignetting" : [ camera_physical.optical_vignetting if use_camera_physical else None ], + "camera_physical_rolling_shutter_duration" : [ camera_physical.rolling_shutter_duration if use_camera_physical else None ], + "camera_physical_rolling_shutter_mode" : [ camera_physical.rolling_shutter_mode if use_camera_physical else None ], + "camera_physical_shutter_angle" : [ camera_physical.shutter_angle if use_camera_physical else None ], + "camera_physical_shutter_offset" : [ camera_physical.shutter_offset if use_camera_physical else None ], + "camera_physical_shutter_speed" : [ camera_physical.shutter_speed if use_camera_physical else None ], + "camera_physical_specify_focus" : [ camera_physical.specify_focus if use_camera_physical else None ], + "camera_physical_specify_fov" : [ camera_physical.specify_fov if use_camera_physical else None ], + "camera_physical_subdivs" : [ camera_physical.subdivs if use_camera_physical else None ], + "camera_physical_target_distance" : [ camera_physical.target_distance if use_camera_physical else None ], + "camera_physical_targeted" : [ camera_physical.targeted if use_camera_physical else None ], + "camera_physical_type" : [ camera_physical.type if use_camera_physical else None ], + "camera_physical_use_dof" : [ camera_physical.use_dof if use_camera_physical else None ], + "camera_physical_use_moblur" : [ camera_physical.use_moblur if use_camera_physical else None ], + "camera_physical_vertical_offset" : [ camera_physical.vertical_offset if use_camera_physical else None ], + "camera_physical_vignetting" : [ camera_physical.vignetting if use_camera_physical else None ], + "camera_physical_white_balance" : [ camera_physical.white_balance if use_camera_physical else None ], + "camera_physical_zoom_factor" : [ camera_physical.zoom_factor if use_camera_physical else None ], + "settings_camera_auto_corrections_mode" : [ settings_camera.auto_corrections_mode ], + "settings_camera_auto_exposure" : [ settings_camera.auto_exposure ], + "settings_camera_auto_exposure_compensation" : [ settings_camera.auto_exposure_compensation ], + "settings_camera_auto_fit" : [ settings_camera.auto_fit ], + "settings_camera_auto_white_balance" : [ settings_camera.auto_white_balance ], + "settings_camera_curve" : [ settings_camera.curve ], + "settings_camera_dist" : [ settings_camera.dist ], + "settings_camera_dont_affect_settings" : [ settings_camera.dont_affect_settings ], + "settings_camera_fov" : [ settings_camera.fov ], + "settings_camera_height" : [ settings_camera.height ], + "settings_camera_image_planes" : [ settings_camera.image_planes ], + "settings_camera_type" : [ settings_camera.type ], + "M_cam_from_uv_00" : [ M_cam_from_uv_[0,0] ], + "M_cam_from_uv_01" : [ M_cam_from_uv_[0,1] ], + "M_cam_from_uv_02" : [ M_cam_from_uv_[0,2] ], + "M_cam_from_uv_10" : [ M_cam_from_uv_[1,0] ], + "M_cam_from_uv_11" : [ M_cam_from_uv_[1,1] ], + "M_cam_from_uv_12" : [ M_cam_from_uv_[1,2] ], + "M_cam_from_uv_20" : [ M_cam_from_uv_[2,0] ], + "M_cam_from_uv_21" : [ M_cam_from_uv_[2,1] ], + "M_cam_from_uv_22" : [ M_cam_from_uv_[2,2] ], + "M_proj_00" : [ M_proj_[0,0] ], + "M_proj_01" : [ M_proj_[0,1] ], + "M_proj_02" : [ M_proj_[0,2] ], + "M_proj_03" : [ M_proj_[0,3] ], + "M_proj_10" : [ M_proj_[1,0] ], + "M_proj_11" : [ M_proj_[1,1] ], + "M_proj_12" : [ M_proj_[1,2] ], + "M_proj_13" : [ M_proj_[1,3] ], + "M_proj_20" : [ M_proj_[2,0] ], + "M_proj_21" : [ M_proj_[2,1] ], + "M_proj_22" : [ M_proj_[2,2] ], + "M_proj_23" : [ M_proj_[2,3] ], + "M_proj_30" : [ M_proj_[3,0] ], + "M_proj_31" : [ M_proj_[3,1] ], + "M_proj_32" : [ M_proj_[3,2] ], + "M_proj_33" : [ M_proj_[3,3] ] }) + + df_camera_parameters = df_camera_parameters.append(df_camera_parameters_) + + df_camera_parameters.to_csv(args.out_file, index=False) + + + +print("[HYPERSIM: DATASET_GENERATE_CAMERA_PARAMETERS_METADATA] Finished.")