mirror of
https://github.com/Digital-Naturalism-Laboratories/Mothbox.git
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73 lines
2.9 KiB
Python
73 lines
2.9 KiB
Python
import subprocess
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import os
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import time
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script_path = r"c:/Users/andre/Documents/GitHub/Mothbox/AI/Mothbot/Mothbot_Detect.py" # Update this with your actual script path
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nightly_deployment_input_paths = [
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\Les_BeachPalm_hopeCobo_2025-06-20",
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\AzueroSuperD_OriaNursery_Nursery_dobleParina_2025-02-05",
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\AzueroSuperD_OriaNursery_Nursery_prizecrab_2025-02-05",
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\AzueroSuperD_OriaNursery_Nursery_wingedHapuku_2025-02-05",
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\Indonesia_Les_BeachPalm_grupoKite_2025-06-23",
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r"g:\Shared drives\Mothbox Management\Testing\ExampleDataset\Indonesia_Les_WilanTopTree_HopeCobo_2025-06-25",
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]
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YOLO_MODEL=r"../trained_models/yolo11m_4500_imgsz1600_b1_2024-01-18/weights/yolo11m_4500_imgsz1600_b1_2024-01-18.pt"
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IMGSZ=1600# Should be same imgsz as used in training for best results!
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GEN_BOT_DET_EVENIF_HUMAN_EXISTS=True #if we encounter a human detection, but still want a parallel bot detection, make this true
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OVERWRITE_PREV_BOT_DETECTIONS=False #if true, if there are previous machine detections, it will overwrite those machine detections with our current ones. This script should NEVER overwrite a human detection
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#You should always leave Gen_Thumbnails as true. It will intelligently detect if a thumbnail exists and skip it if need be.
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GEN_THUMBNAILS=True
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i=0
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def time_it(func):
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"""A decorator to time the execution of a function.
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Args:
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func: The function to be timed.
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Returns:
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A wrapper function that executes the given function and prints the execution time.
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"""
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def wrapper(*args, **kwargs):
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start_time = time.time() # Record the start time
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result = func(*args, **kwargs) # Execute the function
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end_time = time.time() # Record the end time
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execution_time = end_time - start_time # Calculate the elapsed time
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print(f"Function '{func.__name__}' took {execution_time:.4f} seconds to execute.")
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return result # Return the original function's result
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return wrapper
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start_time_overall = time.time()
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for input_path in nightly_deployment_input_paths:
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print("starting to process: "+input_path)
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subprocess.run([
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"python", script_path,
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"--input_path", input_path,
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"--yolo_model", YOLO_MODEL,
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"--imgsz", str(IMGSZ)
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], check=True)
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i=i+1
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print("processed "+str(i)+" folders.")
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print("just finished processing "+input_path)
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end_time_overall = time.time()
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total_execution_time = end_time_overall - start_time_overall
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hours = int(total_execution_time // 3600)
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minutes = int((total_execution_time % 3600) // 60)
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seconds = total_execution_time % 60
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print(f"Overall script execution took {hours:02d}:{minutes:02d}:{seconds:.4f} (HH:MM:SS.SSSS)")
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