MiDaS
deeplearning4j-examples
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| MiDaS | deeplearning4j-examples | |
|---|---|---|
| 27 | - | |
| 4,089 | 2,268 | |
| 4.1% | - | |
| 2.4 | 7.7 | |
| 2 months ago | over 1 year ago | |
| Python | Java | |
| MIT License | GNU General Public License v3.0 or later |
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MiDaS
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How to Estimate Depth from a Single Image
The checkpoint below uses MiDaS, which returns the inverse depth map, so we have to invert it back to get a comparable depth map.
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Distance estimation from monocular vision using deep learning
Hi, I have made use of the KITTI dataset for this, and yes it depends on objects of know sizes. Here I have defined the following classes: Car, Van, Truck, Pedestrian, Person_sitting, Cyclist, Tram, Misc, or DontCare and the predictions are pretty accurate for those classes. Even if it's not the same class, it still recognizes the object since I have made use of the coco names dataset here and that is used along with YOLO for object detection. And there are several already implemented projects that make use of deep learning models trained on 2D datasets to predict 3D distance. This was one of my inspirations for this project: https://blogs.nvidia.com/blog/2019/06/19/drive-labs-distance-to-object-detection/ Furthermore, there are well-documented and researched papers like DistYOLO or MiDaS that makes use of deep learning for depth estimation
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OMPR V0.6.10 update
-Added AI image depth generator Create your own depth map image at a click of a button. Using the awesome MIDAS3.1 https://github.com/isl-org/MiDaS as the backend and the model "dpt_beit_large_512" for the highest quality depth map. Video and GIF depth map generators coming out next together with the Depth movie player feature.
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AI that converts a regular 2d image to stereoscopic
It uses MiDaS. That extension may be the most accessible way to use it at home. IDK.
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Idea: training on magiceye images
Here's the project homepage https://github.com/isl-org/MiDaS
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MiDaS v3_1 and DiscoDiffusion
The problem came up after MiDaS updated to version V3_1 on Dec 24th. Although the fix works fine, with the new version there are many changes, which for me produces slightly different results. I would like to able to produce results like before. I still clone the MiDaS repo, but then set it back to the last commit before the changes in december, which is 66882994a432727317267145dc3c2e47ec78c38a.
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File not found error
try: from midas.dpt_depth import DPTDepthModel except: if not os.path.exists('MiDaS'): gitclone("https://github.com/isl-org/MiDaS.git") gitclone("https://github.com/bytedance/Next-ViT.git", f'{PROJECT_DIR}/externals/Next_ViT') if not os.path.exists('MiDaS/midas_utils.py'): shutil.move('MiDaS/utils.py', 'MiDaS/midas_utils.py') if not os.path.exists(f'{model_path}/dpt_large-midas-2f21e586.pt'): wget("https://github.com/intel-isl/DPT/releases/download/1_0/dpt_large-midas-2f21e586.pt", model_path) sys.path.append(f'{PROJECT_DIR}/MiDaS')
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A quick demo to show how structurally coherent depth2img is compared to img2img using Automatic1111.
Cool. The repo for MiDaS is here. https://github.com/isl-org/MiDaS You can see that they partially trained the model on 3D movies Here's a list of the movies that were used to train it. I wonder if they'll be training a MiDaS v 4.0 as things have moved on quite a bit since it was released in Apr 2021?
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Boosting Monocular Depth repo
We present a stand-alone implementation of our Merging Operator. This new repo allows using any pair of monocular depth estimations in our double estimation. This includes using separate networks for base and high-res estimations, using networks not supported by this repo (such as Midas-v3), or using manually edited depth maps for artistic use. This will also be useful for scientists developing CNN-based MDE as a way to quickly apply double estimation to their own network. For more details please take a look here.
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DepthViewer is now live on Steam :)
I'll make the feature to export only the depthmap .png file. If you need the depthmap .png right now you can use the MiDaS python script.
deeplearning4j-examples
We haven't tracked posts mentioning deeplearning4j-examples yet.
Tracking mentions began in Dec 2020.
What are some alternatives?
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DenseDepth - High Quality Monocular Depth Estimation via Transfer Learning
downlords-faf-client - Official client for Forged Alliance Forever
stablediffusion - High-Resolution Image Synthesis with Latent Diffusion Models
Deeplearning4j - Suite of tools for deploying and training deep learning models using the JVM. Highlights include model import for keras, tensorflow, and onnx/pytorch, a modular and tiny c++ library for running math code and a java based math library on top of the core c++ library. Also includes samediff: a pytorch/tensorflow like library for running deep learning using automatic differentiation.
DiverseDepth - The code and data of DiverseDepth
datascience - Curated list of Python resources for data science.
Insta-DM - Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency (AAAI 2021)
U-2-Net - The code for our newly accepted paper in Pattern Recognition 2020: "U^2-Net: Going Deeper with Nested U-Structure for Salient Object Detection."
consistent_depth - We estimate dense, flicker-free, geometrically consistent depth from monocular video, for example hand-held cell phone video.