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improve README to include the visualization portion #51

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Jun 30, 2024
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improve README to include the visualization portion #51

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27 changes: 24 additions & 3 deletions README.md
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Original file line number Diff line number Diff line change
Expand Up @@ -132,8 +132,8 @@ For quickly running this, we have already prepared and exported the training dat


```sh
mkdir DATADIR
gsutil -m cp -r gs://dl-book/chapter-1/dnn_planet_wo_indices/* DATADIR
mkdir path/to/your/project/data
gsutil -m cp -r gs://dl-book/chapter-1/dnn_planet_wo_indices/* path/to/your/project/data
```

The parent folder (if you run `gsutil -m cp -r gs://dl-book/chapter-1/* DATADIR`) has several dataset inside it. We use `dnn_planet_wo_indices` here because it has lightweight data and would be much faster to run. If you want to test U-Net model, you can use `unet_256x256_planet_wo_indices` folder instead. Each of these have training, testing, and validation sub-folder inside them.
Expand Down Expand Up @@ -282,7 +282,7 @@ import glob
image_files_list = []
json_file = None

for f in glob.glob(f"{IMGDIR}/*"):
for f in glob.glob(f"{IMAGEDIR}/*"):
if f.endswith(".tfrecord.gz"):
image_files_list.append(f)
elif f.endswith(".json"):
Expand Down Expand Up @@ -438,6 +438,27 @@ Once the file is available on GCP, you can then upload to earthengine using `ear
earthengine upload image --asset_id={config.EE_OUTPUT_ASSET}/{config.OUTPUT_NAME} --pyramiding_policy=mode {OUTPUT_GCS_PATH} {json_file}
```

Note: Since this requires to use GCP and enable billing, we have hosted the prediction in the GCP so you don't have to. To use this prediction from GCP and upload to GEE, first make sure you are authenticated to earthengine using (learn more [here](https://developers.google.com/earth-engine/guides/auth) to use different authentication techniques):

```sh
earthengine authenticate
```

After that, let's say you want to upload it to your GEE asset to path say with `config.EE_OUTPUT_ASSET` as `users/biplov/aces_test` and `config.OUTPUT_NAME` as `prediction_dnn_v1` (you can directly use `{config.EE_OUTPUT_ASSET}` and `{config.OUTPUT_NAME}` as shown above), then do:

```sh
earthengine upload image --asset_id=users/biplov/aces_test/prediction_dnn_v1 --pyramiding_policy=mode gs://dl-book/chapter-1/prediction/prediction_dnn_v1.TFRecord gs://dl-book/chapter-1/images/image_2021mixer.json
```

This will give the message similar to below

```sh
Started upload task with ID: T3FMGOOXIXJKEAYXPS77MWDB
```

You can then go to [GEE](https://code.earthengine.google.com/) and check your `Tasks` tab to see that task with the given ID. Once complete, you can use this [script](https://code.earthengine.google.com/98960bd93d59d4236ecc7da02bb95dbb) to visualize your result. You can replace the asset with your own.


***Note: The inferencing is also available on this [notebook](https://github.com/SERVIR/servir-aces/blob/main/notebook/Rice_Mapping_Bhutan_2021.ipynb), scroll to `Inference using Saved U-Net Model` or `Inference using Saved DNN Model` depending upon which model you're using.***

## Contributing
Expand Down
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