Merge branch 'release-cleanup' of https://github.com/fxia22/gibsonv2 into release-cleanup

docs/installation.md

@@ -50,7 +50,7 @@ First, create a folder to contain all the iGibson's assets (robotic agents, obje
 
 Second, you can download our robot models and objects from [here](https://storage.googleapis.com/gibson_scenes/assets_igibson.tar.gz) and unpack it in the assets folder.
 
-Third, you need to download some large 3D reconstructed real-world environments (houses, offices) from our dataset for your agents to be trained in. Create a new folder for those environments and set the path in `your_installation_path/gibson2/global_config.yaml` (default and recommended: `your_installation_path/gibson2/assets/dataset`). You can get access and download the full Gibson and iGibson (interactive furniture) datasets by filling up the following [license agreement](https://forms.gle/YTbzXjNtmmsra9KY6). Alternatively, you can download a single [high quality small environment](https://storage.googleapis.com/gibson_scenes/Rs.tar.gz), R's, together with a [fully interactive version](https://storage.googleapis.com/gibson_scenes/Rs_interactive.tar.gz). 
+Third, you need to download some large 3D reconstructed real-world environments (houses, offices) from our dataset for your agents to be trained in. Create a new folder for those environments and set the path in `your_installation_path/gibson2/global_config.yaml` (default and recommended: `your_installation_path/gibson2/dataset`). You can get access and download the full Gibson and iGibson (interactive furniture) datasets by filling up the following [license agreement](https://forms.gle/YTbzXjNtmmsra9KY6). Alternatively, you can download a single [high quality small environment](https://storage.googleapis.com/gibson_scenes/Rs.tar.gz), R's, together with a [fully interactive version](https://storage.googleapis.com/gibson_scenes/Rs_interactive.tar.gz).
 
 Alternatively, the robot and object models, together with the R's interactive and non-interactive versions can be downloaded and extracted in the assets folder indicated in `your_installation_path/gibson2/global_config.yaml` with a single command:
 

gibson2/core/render/cpp/Mesh_renderer.cpp

@@ -472,7 +472,7 @@ public:
         glBindTexture(GL_TEXTURE_2D, color_tex_semantics);
         glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, width, height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
         glBindTexture(GL_TEXTURE_2D, color_tex_3d);
-        glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA, width, height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
+        glTexImage2D(GL_TEXTURE_2D, 0, GL_RGBA32F, width, height, 0, GL_RGBA, GL_UNSIGNED_BYTE, NULL);
         glBindTexture(GL_TEXTURE_2D, depth_tex);
         glTexImage2D(GL_TEXTURE_2D, 0, GL_DEPTH24_STENCIL8, width, height, 0, GL_DEPTH_STENCIL, GL_UNSIGNED_INT_24_8, NULL);
         glBindFramebuffer(GL_FRAMEBUFFER, fbo);
@@ -517,7 +517,7 @@ public:
         glBindTexture(GL_TEXTURE_2D_MULTISAMPLE, color_tex_semantics);
         glTexImage2DMultisample(GL_TEXTURE_2D_MULTISAMPLE, 4, GL_RGBA, width, height, GL_TRUE);
         glBindTexture(GL_TEXTURE_2D_MULTISAMPLE, color_tex_3d);
-        glTexImage2DMultisample(GL_TEXTURE_2D_MULTISAMPLE, 4, GL_RGBA, width, height, GL_TRUE);
+        glTexImage2DMultisample(GL_TEXTURE_2D_MULTISAMPLE, 4, GL_RGBA32F, width, height, GL_TRUE);
         glBindTexture(GL_TEXTURE_2D_MULTISAMPLE, depth_tex);
         glTexImage2DMultisample(GL_TEXTURE_2D_MULTISAMPLE, 4, GL_DEPTH24_STENCIL8, width, height, GL_TRUE);
         glBindFramebuffer(GL_FRAMEBUFFER, fbo);

gibson2/data_utils/generate_data.py

@@ -3,7 +3,7 @@ import ctypes as ct
 import cv2
 import sys
 import argparse
-from gibson2.data.datasets import ViewDataSet3D
+from gibson2.data_utils.datasets import ViewDataSet3D
 import torch
 from torchvision import datasets, transforms
 from torch.autograd import Variable

gibson2/global_config.yaml

@@ -1,2 +1,2 @@
 assets_path: assets # put either absolute path or relative to current directory
-dataset_path: assets/dataset
+dataset_path: dataset

gibson2/learn/train_fillers.py

@@ -8,7 +8,7 @@ from torchvision import datasets, transforms
 import torch.backends.cudnn as cudnn
 from torch.autograd import Variable
 import torchvision.utils as vutils
-from gibson2.data.datasets import PairDataset
+from gibson2.data_utils.datasets import PairDataset
 from gibson2.learn.completion import CompletionNet, identity_init, Perceptual
 from tensorboardX import SummaryWriter
 from datetime import datetime