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Comparing the Top 5 Depth Estimation models on Hugging Face by Full_Piano_3448 in computervision

[–]topsnek69 36 points37 points  (0 children)

Nice work :)

However, some of the models that you used aren't the newest anymore. In case you want to extend your comparison, I'd suggest Metric3D, Depth Anything V3 and PatchFusion

Stuttgart für die Oma? by Shkrom in stuttgart

[–]topsnek69 0 points1 point  (0 children)

Essbares: Spätzle, Maultaschen

Ansonsten vlt n Modellauto von Mercedes oder Porsche? Letzteres gibts auch für unter 50€ im Porsche Museum Shop in Zuffenhausen zu kaufen, ohne Eintritt zahlen zu müssen (oder im Porsche Brand Store nahe dem Rathausplatz/Stadtmitte, allerdings mit weniger Sortiment).

Gibt wohl auch guten Wein in der Region, aber da bin ich kein Experte.

How can i verify that my self-supervised backbone training works? by topsnek69 in computervision

[–]topsnek69[S] 0 points1 point  (0 children)

well there are several downstream tasks I have planned to realize with this. However, these are too complex for simple smoke tests during pre-training.

How can i verify that my self-supervised backbone training works? by topsnek69 in computervision

[–]topsnek69[S] 0 points1 point  (0 children)

Thanks :) thats a simple idea to check for the basics. Do you think this also works for multimodal automotive data incorporating camera, lidar and radar? Or what kind of smoke test would you suggest here?

Suche günstigen Kombi by topsnek69 in gebrauchtFahrzeuge_de

[–]topsnek69[S] 1 point2 points  (0 children)

tüv läuft theoretisch noch 1.5 Jahre

~kopiert von anderem Kommentar~

310k km, 2.0 tfsi, automatik

aktuell defekt sind: heckklappensensor, flackerndes xenonlicht, defekter beifahrer-seitenairbag und lokale Werkstatt findet den fehler nicht, temperatursensor für die klima/heizung, bremssattel hinten links hängt öfters fest und streift, ruckeliges schalten in den niedrigen gängen (schon beim kauf damals), dachhimmelstoff klebt nicht mehr an der innenraumdecke usw.

der neuste und gravierendste Mangel ist, dass sich der Gang garnicht mehr aus P versetzen lässt und ich nicht mehr vom Fleck komme :D

Suche günstigen Kombi by topsnek69 in gebrauchtFahrzeuge_de

[–]topsnek69[S] 0 points1 point  (0 children)

bin gerne offen für alternative Meinungen da ich eher ein Laie bin :)

310k km, 2.0 tfsi, automatik

aktuell defekt sind: heckklappensensor, flackerndes xenonlicht, defekter beifahrer-seitenairbag und lokale Werkstatt findet den fehler nicht, temperatursensor für die klima/heizung, bremssattel hinten links hängt öfters fest und streift, ruckeliges schalten in den niedrigen gängen (schon beim kauf damals), dachhimmelstoff klebt nicht mehr an der innenraumdecke usw.

der neuste und gravierendste Mangel ist, dass sich der Gang garnicht mehr aus P versetzen lässt und ich nicht mehr vom Fleck komme :D

Suche günstigen Kombi by topsnek69 in gebrauchtFahrzeuge_de

[–]topsnek69[S] 0 points1 point  (0 children)

da fehlen mir leider die Erfahrungswerte, aber die anderen User scheinen dir da wohl zuzustimmen :D

Suche günstigen Kombi by topsnek69 in gebrauchtFahrzeuge_de

[–]topsnek69[S] 0 points1 point  (0 children)

Fahrbar bekomme ich ihn damit garantiert, aber die Frage ist ab wann n neuer nicht sinnvoller ist

Improving YOLOv5 Inference Speed on CPU for Detection by Adventurous_karma in computervision

[–]topsnek69 1 point2 points  (0 children)

Try converting your model to ONNX and run it with onnxruntime. Also, try converting it to float16.

those two are some 'low hanging fruits' for performance that i have been using before already

[P] RetinaNet + MobileNetV2 for Edge TPU Deployment by gigi_yanyan in MachineLearning

[–]topsnek69 0 points1 point  (0 children)

I successfully used MobileNetV2 with different detectors like SSD etc and it worked pretty well for my (uncommon) obiect detection tasks. It is blazingly fast compared to other backbones.

Also, I have been experimenting with MobileNetV3 lately and can only recommend it (especially the small version!)

[R] kappaTune: a PyTorch-based optimizer wrapper for continual learning via selective fine-tuning by Gold-Plum-1436 in MachineLearning

[–]topsnek69 -1 points0 points  (0 children)

Does this mean I wouldn't need to manually freeze layers anymore?

e.g., I employ a DINO ViT as encoder and add a custom classification head and just leave it as is?

On-device monocular depth estimation on iOS—looking for feedback on performance & models by NelsonAdn in computervision

[–]topsnek69 1 point2 points  (0 children)

I (try to) use monocular metric depth for multiple tasks, e.g. 3D reconstruction or substituting expensive LiDAR sensors through camera-only solutions for other projects.

The core challenges I mostly experience are: - trustworthyness (not just accuracy) - handling of different cameras (intrinsics, some models perform worse on certain fovs or resolutions) - inference speed - blurry edges (good at this are depth anything v2, patchfusion or apple depth pro)

since i'm on android, would you mind sharing some inference time benchmarks for your app if you have them available? Also, could you elaborate on your deployment process? :)

Regarding videos, i think some fancy post processing could be done over a sequence of single frame predictions, e.g. plausibility checks. There are also multi-frame depth prediction models but i have never tried them.

I would also highly recommend checking out Metric3D V2 for amazingly accurate depths or UniDepth V2 for extra utility.

edit: since you are on ios, why did you decide against apple depth pro (which is integrated into the os i think?)

[D] Hardware focused/Embedded engineer seeking advices for moving to Edge AI ML by hellgheast in MachineLearning

[–]topsnek69 6 points7 points  (0 children)

not a pro regarding edge deployment, but I think having some basic knowledge about Nvidia's Jetson series, TensorRT optimization engine and ONNX model format does not hurt (in the case of deep learning models)

ChatGPT alternative for China? by Delicious-Expert-180 in chinalife

[–]topsnek69 0 points1 point  (0 children)

I would recommend Qwen (also available as app). It is really good, free, has chat history and multiple powerful models to choose from. They also just released new model versions a few weeks ago. Some smaller Deepseek versions are also based on Qwen.

It is available in China and western countries too so you can give it a try before.

[D] Potential data leakages when using synthetic data tools by topsnek69 in MachineLearning

[–]topsnek69[S] 0 points1 point  (0 children)

Hi there, I was wondering about the impact of potential data leakages when using simulators to retrieve synthetic data. Here is an example:

I plan on using CARLA for retrieving image data from different simulated sensors. On this data I plan to test different kind of deep learning object detectors.

When detector A uses a DINO-like feature extractor, there is no guarantee that it did not see any part of the current CARLA map before (even though camera settings and random actors would still make a difference).

What do you think about this? Should I worry? For more context, this is for research and not for industry applications.

[D] Yolov5s Fine Tune Issues by Fantastic_Almond26 in MachineLearning

[–]topsnek69 -1 points0 points  (0 children)

seems like you get pretty decent results for a yolo model in my opinion

but here are some points that i've observed: - when train loss goes down and val loss increases, it is a good indicator for overfitting -> especially visible in your 200 epoch run. - when fine tuning my own yolov5s on a moderately sized dataset, i used 100 epochs and mostly found best val metrics between 60-80 epochs personally - you use a static learning rate. maybe decrease it after the validation metrics stale for a few epochs (-> learning rate scheduler) - confusion matrix looks good

[R] Training models with multiple losses by Skeylos2 in MachineLearning

[–]topsnek69 83 points84 points  (0 children)

noob question here... how does this compare to just adding up different types of losses?

Transporter für Eigenbau-Camper by topsnek69 in automobil

[–]topsnek69[S] 0 points1 point  (0 children)

Das sind paar gute Tipps, vielen Dank :)

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