def sort_camera_trap_images(unsorted_dir):
json_name = os.path.dirname(unsorted_dir) + ".json"
snapcat_database_dir = os.path.join(unsorted_dir, json_name)
snapcat_json = json_database.JSONDatabase(snapcat_database_dir)
burst.create_bursts(snapcat_json, unsorted_dir)
segmentation.segment_images(snapcat_json)
label_images.label_images(snapcat_json)
user_label_image.user_label_images_burst(snapcat_json)
generate_report.generate_report(snapcat_json, unsorted_dir)
def sort_camera_trap_images(unsorted_dir):
json_name = os.path.basename(os.path.dirname(unsorted_dir)) + ".json"
snapcat_database_dir = os.path.join(unsorted_dir, json_name)
snapcat_json = json_database.JSONDatabase(snapcat_database_dir)
burst.create_bursts(snapcat_json, unsorted_dir)
#segmentation.segment_images( snapcat_json )
#label_images( snapcat_json )
# TODO make sure this is working well to deliver to Island conservation.
# make sure the label is saved in the dataset
user_label_image.user_label_images_burst(snapcat_json)
generate_report.generate_report(snapcat_json, unsorted_dir)
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--image_dir", help="will list all the images within this directory and have user label them", default="")
parser.add_argument("--json_dir", help="path to the json database for images" )
parser.add_argument("--gif", help="display all images from burst or not", default="false" )
args = parser.parse_args()
snapcat_json = json_database.JSONDatabase( args.json_dir )
image_list = list_all_jpgs ( args.image_dir )
print( "gif", args.gif.lower() )
if args.gif.lower() == "true":
user_label_images_burst( snapcat_json )
else:
user_label_images_single( snapcat_json, image_list )
print("cat")
snapcat_json.update(
image, "classifier_label", "cat"
) #TODO - classifier_label will be associated with an area of interest
elif results[i] >= settings.sort_image[
'not_cat_confidence_threshold'] and labels[
i] == 'not cats':
print("not cat")
snapcat_json.update(
image, "classifier_label", "not_cat"
) #TODO - classifier_label will be associated with an area of interest
else:
print("unsure")
snapcat_json.update(
image, "classifier_label", "unsure"
) #TODO - classifier_label will be associated with an area of interest
break
snapcat_json.save()
if __name__ == "__main__":
parser = argparse.ArgumentParser()
parser.add_argument("--json_dir",
help="path to the json database for images")
args = parser.parse_args()
snapcat_json = json_database.JSONDatabase(args.json_dir)
label_images(snapcat_json)