Animl update and wild_demo #59
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updating wild demo to reflect master
Revert "updating wild demo to reflect master"
The demo branch was created hard and fast and these commits make the demo portion more modular in the sense that with merely a few extra lines to the config, you can make fetch_and_alert run the necessary portions to allow the output to be visualized. Currently, one must run this version of fetch_and_alert and simultaneously run display.py with the same config file as fetch and alert to work. display.py is the main function and visualize_helper.py contain some functions that get called in fetch_and_alert to ensure the images are in the proper place and format for display.py to reach them.
Was called visualize_output now called visualize_helper
The script was not writing the log to a file, only to the terminal and was logging duplicated lines. It needed to be initialized before calling the classifier and detector initializers because when those got called first, they introduced their own logging handlers that overrode the one I created. Also the force=True needed to be added so that the log file would actually be created
There's a few "too many variables" and "unable to import" errors but I'm ignoring those
We trained a new model 'southwest_v3.pt' that performs better on cougars than the previous model, but the animl-py on pypi can only handle h5 models. Cougarvision had to be updated to be compatible with the updates that have been made to animl-py on github where there exists the capability to use .pt models. It was mostly function name changes and movement, and the updates only affected fetch_and_alert.py for loading the classifier model and detect_img.py.
The example config file was missing some of the parameters needed by cougarvision wild_demo update. This config file now exposes the color for the bounding box, sending email alerts, the time between fetch_and_alert function call, and changed the names of the config values for dev and consumer emails.
There was an old animl function called parse_results that prepared the classification output for alert sending this has been depricated and that old function is no longer necessary
the example config needed to be updated to reflect changes
wild_demo had animl_update created based off wild_demo, need to be merged before pr to master
tkswanson
reviewed
Mar 27, 2024
tkswanson
reviewed
Mar 27, 2024
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this is fine but we want to avoid species-specific nomenclature going forward, switch to "detections"
tkswanson
reviewed
Mar 27, 2024
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| from cougarvision_utils.cropping import draw_bounding_box_on_image | ||
| from cougarvision_utils.alert import smtp_setup, send_alert | ||
| from cougarvision_visualize.visualize_helper import get_last_file_number | ||
| from cougarvision_visualize.visualize_helper import create_folder | ||
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| with open("config/cameratraps.yml", 'r') as stream: |
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This should not be part of the module, this should be run once from the main function
tkswanson
reviewed
Mar 27, 2024
| @@ -68,11 +70,21 @@ def request_strikeforce(username, auth_token, base, request, parameters): | |||
| strikeforce | |||
| ''' | |||
| call = base + request + "?" + parameters | |||
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This should be a function that is called, it shouldn't just run every time the module is opened
tkswanson
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Mar 27, 2024
| return max_num | ||
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| def create_folder(folder_path): |
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this function can be replaced with os.makedirs(exist_ok=True)
tkswanson
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Mar 27, 2024
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| # Set interval for checking in | ||
| CHECKIN_INTERVAL = CONFIG['checkin_interval'] | ||
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| print("Loading classifier") |
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All this should be in main()
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this pull request reflects a few updates which should be in different pull requests, but they are in one. there is now capability to run a visualization of the output in a demo setting by changing a few config values, and allows for the usage of .pt classifier models. there is also logging to a file that now takes place.