added detectree example notebook

[shmh40]

To do:

• Read in model weights with intake (is this possible @acocac ?
• Provide graphical interface with leafmap so users can see predictions and tiff geographically
• Small tidy possible - extend summary, move comments to markdown

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[shmh40]

• Updated notebook with interactive leafmap
• This currently works for shapefiles, but I cannot make it work for tiffs, even using the example from the documentation

[shmh40]

Added code so forest-modelling-detectree-v2 will run on cpu

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acocac commented on 2021-09-21T09:35:18Z
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Great description! I would add the hyperlink to Mask R-CNN and mention it's available through the detectron2 framework.

shmh40 commented on 2021-09-23T09:29:43Z
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Added hyperlink

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acocac commented on 2021-09-21T09:35:19Z
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There are some libraries that the notebook doesn't longer need and others I added for interactive plotting. I would suggest to replace the original cells of this section by the following ones:

Cell 1:

## install detectron2
!python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'
install geospatial libraries
!pip -q install geopandas

!pip -q install rasterio

!pip -q install fiona

!pip -q install shapely
install intake plugins
!pip -q install git+https://github.com/ESM-VFC/intake_zenodo_fetcher.git

Cell 2:

import cv2

from PIL import Image

import os

import numpy as np

import urllib.request

import glob

intake library and plugin
import intake

from intake_zenodo_fetcher import download_zenodo_files_for_entry
geospatial libraries
import geopandas as gpd
from rasterio.transform import from_origin

import rasterio.features
import fiona
from shapely.geometry import shape, mapping, box

from shapely.geometry.multipolygon import MultiPolygon
machine learning libraries
from detectron2 import model_zoo

from detectron2.engine import DefaultPredictor

from detectron2.utils.visualizer import Visualizer, ColorMode

from detectron2.config import get_cfg
visualisation
import holoviews as hv

from IPython.display import display

import geoviews.tile_sources as gts
import hvplot.pandas

import hvplot.xarray
hv.extension('bokeh', width=100)

shmh40 commented on 2021-09-23T09:31:15Z
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Agreed

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acocac commented on 2021-09-21T09:35:20Z
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remove

shmh40 commented on 2021-09-23T09:31:04Z
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Done

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acocac commented on 2021-09-21T09:35:20Z
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remove

shmh40 commented on 2021-09-23T09:31:27Z
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Done

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acocac commented on 2021-09-21T09:35:21Z
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remove

shmh40 commented on 2021-09-23T09:31:41Z
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Done

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acocac commented on 2021-09-21T09:35:21Z
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remove

shmh40 commented on 2021-09-23T09:31:54Z
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Done

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acocac commented on 2021-09-21T09:35:22Z
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Before the Load data section, I would provide a sort of project folder structure (a python dictionary) into a new section Set Folder Structure. I provide the cell to add into this new suggestion.

# Define the project main folder
data_folder = './detectree'
Set the folder structure
config = {

'in_geotiff': os.path.join(data_folder, 'input','tiff'),

'in_png': os.path.join(data_folder, 'input','png'),

'model': os.path.join(data_folder, 'model'),

'out_geotiff': os.path.join(data_folder, 'output','raster'),

'out_shapefile': os.path.join(data_folder, 'output','vector'),

}
List comprehension for the folder structure code
[os.makedirs(val) for key, val in config.items() if not os.path.exists(val)]

shmh40 commented on 2021-09-23T09:33:16Z
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Done - thank you

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acocac commented on 2021-09-21T09:35:23Z
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remove as we install intake zenodo fetcher plugin in the Install and load libraries section. Note we don't need to install intake and intake-array as they're already available in environment.yml file of the Environmental AI book.

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acocac commented on 2021-09-21T09:35:23Z
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remove as we are importing intake and intake zenodo in the Install and load libraries section. Also, we aren't longer using tempfile due to the proposed folder structure.

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acocac commented on 2021-09-21T09:35:24Z
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Line #1.    # create a temp dir

remove

shmh40 commented on 2021-09-23T09:58:22Z
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Done

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acocac commented on 2021-09-21T09:35:25Z
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Line #2.    path = tempfile.mkdtemp()

remove

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acocac commented on 2021-09-21T09:35:25Z
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Line #3.    

add

# write a catalog YAML file

shmh40 commented on 2021-09-23T09:58:13Z
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Done

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acocac commented on 2021-09-21T09:35:26Z
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Line #4.    catalog_file = os.path.join(path, 'catalog.yaml')

change:

catalog_file = os.path.join(data_folder, 'catalog.yaml')

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acocac commented on 2021-09-21T09:35:26Z
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Line #15.          urlpath: "{{ CATALOG_DIR }}/Sep_2014_RGB_602500_646600.tif"

change:

urlpath: "{{ CATALOG_DIR }}/input/tiff/Sep_2014_RGB_602500_646600.tif"

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acocac commented on 2021-09-21T09:35:27Z
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Line #1.    # let's investigate the data-array, what is the shape? Bounds? Bands? CRS?

move this text into the markdown of the subheading,

Let's investigate the data-array object, what is the shape? Bounds? Bands? CRS? 

shmh40 commented on 2021-09-23T09:58:01Z
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Done

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acocac commented on 2021-09-21T09:35:28Z
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add some additional text below the subsection heading, for example:

The Mask R-CNN requires images in png format. Let's export the RGB bands to a png file.

shmh40 commented on 2021-09-23T09:57:54Z
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Done

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acocac commented on 2021-09-21T09:35:28Z
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Line #15.    cv2.imwrite('/home/jovyan/lustre_scratch/sepilok_data/spare_pngs/tile_'+str(minx)+'_'+str(miny)+'.png', rgb_rescaled)

change to:

filepath = config['in_png'] + '/' + 'tile_' + str(minx) + '_' + str(miny) + '.png'
cv2.imwrite(filepath, rgb_rescaled)

shmh40 commented on 2021-09-23T09:57:47Z
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Done

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acocac commented on 2021-09-21T09:35:29Z
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Line #1.    filepath = "/home/jovyan/lustre_scratch/sepilok_data/spare_pngs/tile_602500_646600.png"

remove

shmh40 commented on 2021-09-23T09:57:27Z
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Done

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acocac commented on 2021-09-21T09:35:29Z
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Before this section, we can add a new subsection Download the pretrained model with the following cell:

# define the URL to retrieve the model
fn = 'model_final.pth'
url = f'https://zenodo.org/record/5515408/files/{fn}?download=1'
urllib.request.urlretrieve(url, config['model'] + '/' + fn)

shmh40 commented on 2021-09-23T09:57:19Z
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Nice

acocac commented on 2021-09-23T14:45:53Z
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(:

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acocac commented on 2021-09-21T09:35:30Z
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Line #1.    from detectron2.utils.visualizer import ColorMode

remove

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acocac commented on 2021-09-21T09:35:31Z
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Line #2.    from detectron2.engine import DefaultTrainer

remove

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acocac commented on 2021-09-21T09:35:31Z
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Line #3.    from detectron2.config import get_cfg

remove

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acocac commented on 2021-09-21T09:35:32Z
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Line #17.    cfg.MODEL.WEIGHTS = '/home/jovyan/detectron2_live/train_test/output/model_final.pth'

change to:

cfg.MODEL.WEIGHTS = config['model'] + '/model_final.pth'

[shmh40]

Done

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[shmh40]

v4 of the notebook now uploaded with desired changes and some minor amendments to mapping - added code to save the interactive map.

[acocac]

It seems there are some version problems with recent pytorch and detectron2 installed via !python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'. I would suggest to add an extra line above ## install detectron2:

# install pytorch
!pip -q install torch==1.8.0 
!pip -q install torchvision==0.9.0

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[acocac]

(:

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acocac commented on 2021-09-23T14:57:34Z
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It seems there are some version problems with recent pytorch and detectron2 installed via !python -m pip install 'git+https://github.com/facebookresearch/detectron2.git'. I would suggest to add an extra line above ## install detectron2:

# install pytorch
!pip -q install torch==1.8.0 
!pip -q install torchvision==0.9.0

shmh40 commented on 2021-10-09T11:58:10Z
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Done

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acocac commented on 2021-09-23T14:57:34Z
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Line #10.    plot_rgb = int_arr.astype('uint8').hvplot.rgb(

It might worth to investigate how you can change the info displayed in the hover.... can we add some info from the polygons e.g. probability?

shmh40 commented on 2021-10-09T12:33:00Z
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Done!

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acocac commented on 2021-09-23T14:57:35Z
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It might be a good to mention why you export as HTML and not PNG. For instance, you can say:

Let's export the combined map to a HTML file, this allows to keep the interactive plotting in a separate window.

shmh40 commented on 2021-10-09T11:57:42Z
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Done

[acocac]

@shmh40 thanks for implementing the suggestions. I just made a minor comments.
FYI, You don't need to create a new notebook file for each version. Please make the minor changes on forest-modelling-detectree-v4.ipynb . Let me know if you succeed to explore further the hover of hvplot. Otherwise, the notebook is ready to publish!

[shmh40]

Done

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[shmh40]

Done

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[shmh40]

Made final changes, and added function to see confidence score in hvplot. Good to go!

[shmh40]

Done!

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[shmh40]

All changes complete!

[acocac]

Thanks @shmh40, it was great to have your contribution for the forest domain. I hope you learnt some useful python packages for handling geospatial datasets. I made some minor style adjustments to the notebook and now it's good to go (: