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MiDaS Alternatives
Similar projects and alternatives to MiDaS
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stable-diffusion-webui-depthmap-script
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Power Real-Time Data Analytics at Scale. Get real-time insights from all types of time series data with InfluxDB. Ingest, query, and analyze billions of data points in real-time with unbounded cardinality.
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deeplearning4j-examples
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Insta-DM
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consistent_depth
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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."
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multi-subject-render
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InvokeAI
InvokeAI is a leading creative engine for Stable Diffusion models, empowering professionals, artists, and enthusiasts to generate and create visual media using the latest AI-driven technologies. The solution offers an industry leading WebUI, supports terminal use through a CLI, and serves as the foundation for multiple commercial products.
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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.
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xformers
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Graphite
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DPT
Discontinued Dense Prediction Transformers [Moved to: https://github.com/isl-org/DPT] (by intel-isl)
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SaaSHub
SaaSHub - Software Alternatives and Reviews. SaaSHub helps you find the best software and product alternatives
MiDaS reviews and mentions
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Distance estimation from monocular vision using deep learning
For example, here is MiDaS from Intel Research that does monocular depth estimation.
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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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.
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Wow, depth map and img2img are wild
The latter. It uses a pretrained network called MiDaS to estimate image depth. If I'm not mistaken this will produce a depth estimation of the same resolution as the image, and then downsample that to the latent space's dimension (64x64 for a 512x512 image I think) and pass it in as extra conditioning.
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Generate multiple complex subjects on a single image all at once with a depth aware custom extension!
C:\PROGRAMME2\stable_diffusion_automatic1111\stable-diffusion-webui>git clone https://github.com/isl-org/MiDaS.git repositories/midas
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A note from our sponsor - InfluxDB
www.influxdata.com | 28 Mar 2024
Stats
isl-org/MiDaS is an open source project licensed under MIT License which is an OSI approved license.
The primary programming language of MiDaS is Python.