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Thank you again for your work!!
I was able to train your network with my own synthetic data (in the form of the Linemo dataset), evaluate it an visualize the result. So far so good!
Now I want to ch…
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I wanted to also incorporate self-attention into the model to make the example a bit more interesting and fun.
Here's how I am doing it currently:
```python
...
# Second conv block.
x = kera…
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Related issues:
- #6
- #14
- #46
- #97
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## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
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## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
-
## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
-
## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
-
## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
-
## Preprocessing the dataset
The greyscale assigned to each pixel within an image has a value range of 0-255. We will want to flatten (smoosh… scale…) this range to 0-1. To achieve this flattening, we…
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Hello,
in the paper, in page 5, the equation 3 is referenced to 32: "Depth map prediction from a single image using a multi-scale deep network" from Eigen et. al. . But looking at this reference coul…