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Depth Estimation From a Single Image Using Guided Deep Network
Hello,
When I did the evaluation test, I had some problems. I used KITTI dataset segmented by eigen for evaluation, a total of 697 images. Since the code you provided contains some file names that belong to you, I wrote an independent evaluation code. But the results I got are not ideal, and they are very different from the results provided in your paper. I modified my code based on the compute_errors function in the calculate_error.py file in your code. Although the results have improved, there is still a gap with your results.
Based on the demo you provided, I wrote the prediction code to predict 697 images. I used all your operations, including up-sampling, scaling and channel transformation. I save the final result as an .npy file. The detailed process of my evaluation code is as follows:
In the end, the results I got are as follows, which is far from the results in your thesis.
***************** | abs_rel | sq_rel | rms | log_rms | a1 | a2 | a3
first-order result | 0.2913 | 2.1279 | 6.7395 | 0.6446 | 0.5039 | 0.7606 | 0.858
Ref your code | 0.2508 | 1.9023 | 6.6494 | 0.4613 | 0.5662 | 0.814 | 0.9053
Can you give me some suggestions on how I can operate to get the excellent results as provided in your paper.
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