a simple farmbot api focussed on bulk image capture and annotation
comms with the farmbot is via mqtt
pip3 install paho-mqtt
use request_token.py to request an auth token for the farmbot api;
this script writes a creds.py file. do NOT check creds.py in!!
./request_token.py --email YOUR_FARMBOT_EMAIL_LOGIN --password YOUR_PASSWORD
a common use case is the combo of sweeping across the bed capturing images, downloading them all and then run detections
./sweep_bed.py
./download_images.py
./calculate_detections.py
demo use case of move to a position and take a photo
cat ./simple_move_eg.py
import creds
from client import FarmbotClient
client = FarmbotClient(creds.device_id, creds.token)
client.move(200, 700, 0)
client.take_photo()
client.shutdown()
use sweep bed to sweep over entire farm bed taking images
./sweep_bed.py --min-x 0 --max-x 2500 --min-y 0 --max-y 1300 --delta 500 --dry-run
15 [(0, 0), (0, 500), (0, 1000), (500, 1000), (500, 500), (500, 0), (1000, 0), (1000, 500), (1000, 1000), (1500, 1000), (1500, 500), (1500, 0), (2000, 0), (2000, 500), (2000, 1000)]
everything is async so a requested image might be captured by isn't immediately available for download. so when doing sweep captures we download images in bulk. uses the farmbot REST api to download all images and then delete them from cloud storage.
./download_images.py
show a collage with all images for a specific (x, y, z). assumes z=0 if only two args provided.
./show_images_for.py 200 200
run faster rcnn on all images that haven't been run yet. we calculate detections for the image as captured as well as rotated by 90, 180 and 270 degrees.
./calculate_detections.py
./show_detections.py imgs/20181122/140032.jpg
./tail_logs.py