# initialize the Adjusted class -> obj_det_custom_yolo_live.py
adj = Adjusted()
if initial.access_path: # not doing the hardcoded test
try: # allows for a keyboard interrupt
while(True): # continuously run this code until a keyboard interrupt occurs
update = 0 # check to see if the AI ran
if initial.mutex == 1: # check to see if init can access the files
#print("in mutex 1")
asyncio.run(initial.look_for_image()) # look for images in the unaccessed folder -> init.py/look_for_image
if len(initial.queue) > 0:# and initial.mutex == 2: # if there are images to run and AI can access the files
#print("in mutex 2")
adj.AIRun(initial.queue[0]) # run the AI on the first image in the queue -> obj_det_custom_yolo_live.py
#adj.AIRun() # testing purposes only
initial.queue.pop(0) # remove the image we just ran through the AI
initial.mutex = 1 # change locks
update = 1 # make it so we don't try to update the database every time if there is nothing new to add
if update:
img_data = initial.get_img_data() # get the updated data
for img in img_data: # for each image in the dictionary, send any new data to the database
# print(img)
# the second dictionary has entries separated by bounding box (x, y) coordinates (coordinates in reference to image size, not GPS)
for box in img_data[img]: # for each bounding box in the image
#print("box")
# limit entries sent to database to 5, for testing purposes only (everything will work without this, this is only used for proof of concept)
#if i > 5:
# break
# there is other information stored in the initial dictionary that is not the second dictionary, we want to skip over this
#print(type(init.img_data[img][box]))
#print(init.img_data[img][box])
