MiDaS VS GotoBrowser

The checkpoint below uses MiDaS, which returns the inverse depth map, so we have to invert it back to get a comparable depth map.

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

-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.

It uses MiDaS. That extension may be the most accessible way to use it at home. IDK.

Here's the project homepage https://github.com/isl-org/MiDaS

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.

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')

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?

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.

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.

Not really, but it's still 100% playable. There's a fanmade English patch which I've heard is pretty damn good. That said, it's 100 playable without. The UI has a decent bit of icons/English depending on settings, so it's not to hard to figure out. The wiki is great and updated faster than the AL one. I knew jack shit Japanese when I started playing way back when (like 1 semester's worth), and it didn't take long to figure out the basic controls. You do need some kind of VPN for the initial sign up, but after that you can handle it with something like KC3Kai which also keeps track of quests, battles, drops, etc. It's just a Chrome extension, and it helps a lot. On mobile, you can use Gotobrowser to play, tho at least personally I prefer KC3Kai.

Outside of registering, yeah there's an fanmade English patch for it. GotoBrowser is an Android app for the game that works great, dodges the VPN requirement, and also has an English mode. Personally, I use KC3Kai, which is a Chrome extension. It makes actual gameplay a lot easier and basically counts as a VPN. It's super handy, and I'm 100% not biased because I've got it open in another tab as I type this.

For Android users: GotoBrowser (It is currently v2 and still pending for new release)

Some VPNs are blocked, but most are free and you only need to use it to enter a server. It needs to be set to Japan. I'd recommend getting GotoBrowser rather than the official app, and turn on "Gadget Block Bypass". Also, do you have a PC? It's more comfortable to start there. Let me know how it goes.

As far as playing on your phone, do note that the phone version uses the same account as the browser one; no need for a lottery or new account at all. Most people I know who play on their phones, however, use GotoBrowser, though I personally don't play on my phone. Of note is the fact that GotoBrowser technically uses the desktop browser client.

For Android users: GotoBrowser (v2.8r1)

If you didn't know yet, the HTML5 android browser is based on antest1's GotoBrowser

There is a shitty official android app, a way better community-made wrapper of the browser game for mobile and a community-made english patch for the game now.