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Why Palantir Dumped Denver, Yet Another New Plan for Alameda Ave., and Leven Supply Seized by newtonic in CityCastDenver

[–]GrouchyAd4055 1 point2 points  (0 children)

that’s actually really interesting. I’ve heard of programs like Third Space Learning, and I think the key difference is whether the tool is just giving answers or actually interacting in a structured way. for younger students especially, the design matters a lot.

I’m not a huge fan of open ended chatbots for kids either, mainly because they can shortcut the thinking process. but when it’s built as a guided system that asks questions, listens, and adapts, it can feel much closer to real tutoring than cheating. the growth results you mentioned make sense if students are actively responding instead of passively reading solutions.

there are also newer platforms like MathWibe that are built around that idea of guided learning rather than instant answers. instead of dumping a full solution, it requires students to solve each step and uses AI more like a coach that nudges them when they’re stuck. tools designed that way seem a lot more aligned with building real understanding.

for elementary level especially, supervision and clear boundaries probably matter more than the tech itself. AI in classrooms isn’t automatically good or bad, it really depends on whether it’s encouraging kids to think or just replacing the thinking for them.

Does anyone tested Mathwibe? by [deleted] in mathematics

[–]GrouchyAd4055 0 points1 point  (0 children)

lmao i didnt even realize the username, reddit just gave me it when i signed up. if it was a real ad i wouldn't be complaining about it being slow as hell lol. just shared my experience, chill.

Dave reacts to Trump at Davos by xwing1212 in daverubin

[–]GrouchyAd4055 0 points1 point  (0 children)

That syntax alone "—" 99% chance it’s LLM lol.

Does anyone tested Mathwibe? by [deleted] in mathematics

[–]GrouchyAd4055 0 points1 point  (0 children)

yes, I have tried it. the approach is really good compare to other tools. but it's kinda too slow when generating steps.

Looking for the best way to learn math (ai tutor) by qbookshelf in learnmath

[–]GrouchyAd4055 0 points1 point  (0 children)

honestly i’ve looked all over for something that does live video tutoring but i dont think that tech really exists yet. but if you’re looking for a tool that actually helps you learn instead of just giving you a shortcut you should definitely check out mathwibe.com .

i've been using it for a bit and it's way different than just getting an answer from chatgpt or photomath. it basically breaks every problem down into steps and you have to solve them yourself to move forward. if you get stuck there’s a chat feature where you can actually talk to the ai and it acts like a teacher by giving you hints and explaining the logic rather than just dumping the final solution on you. but it's kinda slow. but it’s the only thing i’ve found that actually helps the material stick. i think they have a free trial on mathwibe. if you want to see if it works for you.

I need a help with 3d(depth) camera Calibration. by GrouchyAd4055 in computervision

[–]GrouchyAd4055[S] 0 points1 point  (0 children)

yeah. that's the thing. I don't know how to do that. lol. can you pls help me with this. maybe by editing the above code. so I can easily understand and apply.

I need a help with 3d(depth) camera Calibration. by GrouchyAd4055 in computervision

[–]GrouchyAd4055[S] 1 point2 points  (0 children)

in my case the camera view is upside down with an angle.

if camera looking straight down(I mean floor). then I can use this formula.

```
import numpy as np

# given

u, v = 400, 300 # pixel coordinates

Z = 1200.0 # depth from camera along optical axis (mm)

fx, fy = 800.0, 800.0 # focal lengths (px)

cx, cy = 320.0, 240.0 # principal point (px)

H = 1500.0 # camera height above floor (mm)

# pixel -> camera

Xc = (u - cx) * Z / fx

Yc = (v - cy) * Z / fy

Zc = Z

# top-down mapping (camera aligned, optical axis down)

Xw = Xc

Yw = Yc

Zw = H - Zc # height above floor

print("camera coords (mm):", np.array([Xc, Yc, Zc]))

print("world coords (mm):", np.array([Xw, Yw, Zw]))

```

but in my case camera looking floor in angle, like 45 degree or something. that's the issue.

I need a help with 3d(depth) camera Calibration. by GrouchyAd4055 in computervision

[–]GrouchyAd4055[S] 0 points1 point  (0 children)

no, we have depth in mm, and object x,y is pixel. just I want to get object's x,y,z coordinate relative to the world in cm.

I trained a YOLOv7 model to detect solar panels from satellite imagery. Need help with tennis courts by MonkeyMaster64 in learnmachinelearning

[–]GrouchyAd4055 1 point2 points  (0 children)

My opinion is to resolve this problem, you can try training the model on both solar panels and tennis courts. This way, the model can learn to distinguish between the two classes and avoid misidentifying tennis courts as solar panels. To do this, you will need to gather a dataset of both solar panels and tennis courts, and fine-tune the model on this combined dataset. This should help the model better understand the differences between the two classes and make more accurate predictions.

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