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ZeoD_K: Unexpected Max Depth Values #139
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Hello, I have also encountered the same problem. Can we understand that the maximum depth is a conversion ratio scale from relative distance to absolute distance? If I know the maximum depth of the actual image and input it into the model, does it mean that I can obtain an accurate absolute depth? |
From my understanding, the model returns the estimated absolute depth distance. You can try rescaling it accordingly, but it won't be perform that well. I'd recommend using NYU-KITTI weights instead. It performs better and more consistent, but still not good enough for outdoor (You'll notice this if you do a point cloud reconstruction of the scene with textures). |
Additionally, you can refer to the response in their respective hugging face website link |
Hi, I'm testing the ZoeDepth pretrained models on images captured by highway-side cameras. These images have ground truth depth values that span beyond 300 meters, which I understand exceeds the model's training range (max depth: 80.0 meters).
However, when running the pretrained KITTI model, I consistently get a maximum estimated depth of approximately 5 meters. Below is the code snippet I used:
For comparison, I also tested the NK model. It provides a more reasonable maximum depth estimate, ranging between 30–50 meters, which aligns better with the expected values from the model.Additionally, I tried using the KITTI model weights from Hugging Face
, but the results were similar.
Upon inspecting the model configurations, I noticed potential discrepancies in the uploaded weights:
This configuration suggests a maximum depth of 10.0 meters, which might explain the observed behavior.
Questions/Concerns:
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