VoucherVision / vouchervision /vouchervision_main.py
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Major update. Support for 15 LLMs, World Flora Online taxonomy validation, geolocation, 2 OCR methods, significant UI changes, stability improvements, consistent JSON parsing
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'''
VoucherVision - based on LeafMachine2 Processes
'''
import os, inspect, sys, shutil
from time import perf_counter
# currentdir = os.path.dirname(os.path.dirname(inspect.getfile(inspect.currentframe())))
# parentdir = os.path.dirname(currentdir)
# sys.path.append(parentdir)
# sys.path.append(currentdir)
from vouchervision.component_detector.component_detector import detect_plant_components, detect_archival_components
from vouchervision.general_utils import save_token_info_as_csv, print_main_start, check_for_subdirs_VV, load_config_file, load_config_file_testing, report_config, save_config_file, crop_detections_from_images_VV
from vouchervision.directory_structure_VV import Dir_Structure
from vouchervision.data_project import Project_Info
from vouchervision.LM2_logger import start_logging
from vouchervision.fetch_data import fetch_data
from vouchervision.utils_VoucherVision import VoucherVision, space_saver
from vouchervision.utils_hf import upload_to_drive
def voucher_vision(cfg_file_path, dir_home, path_custom_prompts, cfg_test, progress_report, json_report, path_api_cost=None, test_ind = None, is_hf = True, is_real_run=False):
t_overall = perf_counter()
# Load config file
report_config(dir_home, cfg_file_path, system='VoucherVision')
if cfg_test is None:
cfg = load_config_file(dir_home, cfg_file_path, system='VoucherVision') # For VoucherVision
else:
cfg = cfg_test
# Check to see if there are subdirs
# Yes --> use the names of the subsirs as run_name
run_name, dirs_list, has_subdirs = check_for_subdirs_VV(cfg)
print(f"run_name {run_name} dirs_list{dirs_list} has_subdirs{has_subdirs}")
# Dir structure
if is_real_run:
progress_report.update_overall(f"Creating Output Directory Structure")
print_main_start("Creating Directory Structure")
Dirs = Dir_Structure(cfg)
# logging.info("Hi")
logger = start_logging(Dirs, cfg)
# Check to see if required ML files are ready to use
if is_real_run:
progress_report.update_overall(f"Fetching LeafMachine2 Files")
ready_to_use = fetch_data(logger, dir_home, cfg_file_path)
assert ready_to_use, "Required ML files are not ready to use!\nThe download may have failed,\nor\nthe directory structure of LM2 has been altered"
# Wrangle images and preprocess
print_main_start("Gathering Images and Image Metadata")
Project = Project_Info(cfg, logger, dir_home, Dirs) # Where file names are modified
# Save config file
save_config_file(cfg, logger, Dirs)
# Detect Archival Components
print_main_start("Locating Archival Components")
Project = detect_archival_components(cfg, logger, dir_home, Project, Dirs, is_real_run, progress_report)
# Save cropped detections
crop_detections_from_images_VV(cfg, logger, dir_home, Project, Dirs)
# Process labels
Voucher_Vision = VoucherVision(cfg, logger, dir_home, path_custom_prompts, Project, Dirs, is_hf)
n_images = len(Voucher_Vision.img_paths)
last_JSON_response, final_WFO_record, final_GEO_record, total_tokens_in, total_tokens_out = Voucher_Vision.process_specimen_batch(progress_report, json_report, is_real_run)
total_cost = save_token_info_as_csv(Dirs, cfg['leafmachine']['LLM_version'], path_api_cost, total_tokens_in, total_tokens_out, n_images, dir_home, logger)
t_overall_s = perf_counter()
logger.name = 'Run Complete! :)'
logger.info(f"[Total elapsed time] {round((t_overall_s - t_overall)/60)} minutes")
space_saver(cfg, Dirs, logger)
if is_real_run:
progress_report.update_overall(f"Run Complete!")
Voucher_Vision.close_logger_handlers()
zip_filepath = None
# Create Higging Face zip file
dir_to_zip = os.path.join(Dirs.dir_home, Dirs.run_name)
zip_filename = Dirs.run_name
# Creating a zip file
zip_filepath = make_zipfile(dir_to_zip, zip_filename) ####################################################################################################### TODO Make this configurable
if is_hf:
upload_to_drive(zip_filepath, zip_filename, is_hf, cfg_private=Voucher_Vision.cfg_private, do_upload=True) ###################################### TODO Make this configurable
else:
upload_to_drive(zip_filepath, zip_filename, is_hf, cfg_private=Voucher_Vision.cfg_private, do_upload=False) ##################################### TODO Make this configurable
return {'last_JSON_response': last_JSON_response,
'final_WFO_record': final_WFO_record,
'final_GEO_record': final_GEO_record,
'total_cost': total_cost,
'n_failed_OCR': Voucher_Vision.n_failed_OCR,
'n_failed_LLM_calls': Voucher_Vision.n_failed_LLM_calls,
'zip_filepath': zip_filepath,
}
def make_zipfile(base_dir, output_filename):
# Determine the directory where the zip file should be saved
# Construct the full path for the zip file
full_output_path = os.path.join(base_dir, output_filename)
# Create the zip archive
shutil.make_archive(full_output_path, 'zip', base_dir)
# Return the full path of the created zip file
return os.path.join(base_dir, output_filename + '.zip')
def voucher_vision_OCR_test(cfg_file_path, dir_home, cfg_test, path_to_crop):
# get_n_overall = progress_report.get_n_overall()
# progress_report.update_overall(f"Working on {test_ind+1} of {get_n_overall}")
# Load config file
report_config(dir_home, cfg_file_path, system='VoucherVision')
if cfg_test is None:
cfg = load_config_file(dir_home, cfg_file_path, system='VoucherVision') # For VoucherVision
else:
cfg = cfg_test
# user_cfg = load_config_file(dir_home, cfg_file_path)
# cfg = Config(user_cfg)
# Check to see if there are subdirs
# Yes --> use the names of the subsirs as run_name
run_name, dirs_list, has_subdirs = check_for_subdirs_VV(cfg)
print(f"run_name {run_name} dirs_list{dirs_list} has_subdirs{has_subdirs}")
# for dir_ind, dir_in in enumerate(dirs_list):
# if has_subdirs:
# cfg['leafmachine']['project']['dir_images_local'] = dir_in
# cfg['leafmachine']['project']['run_name'] = run_name[dir_ind]
# Dir structure
print_main_start("Creating Directory Structure")
Dirs = Dir_Structure(cfg)
# logging.info("Hi")
logger = start_logging(Dirs, cfg)
# Check to see if required ML files are ready to use
ready_to_use = fetch_data(logger, dir_home, cfg_file_path)
assert ready_to_use, "Required ML files are not ready to use!\nThe download may have failed,\nor\nthe directory structure of LM2 has been altered"
# Wrangle images and preprocess
print_main_start("Gathering Images and Image Metadata")
Project = Project_Info(cfg, logger, dir_home, Dirs) # Where file names are modified
# Save config file
save_config_file(cfg, logger, Dirs)
# Detect Archival Components
print_main_start("Locating Archival Components")
Project = detect_archival_components(cfg, logger, dir_home, Project, Dirs)
# Save cropped detections
crop_detections_from_images_VV(cfg, logger, dir_home, Project, Dirs)
# Process labels
Voucher_Vision = VoucherVision(cfg, logger, dir_home, None, Project, Dirs)
last_JSON_response = Voucher_Vision.process_specimen_batch_OCR_test(path_to_crop)
if __name__ == '__main__':
is_test = False
# Set LeafMachine2 dir
dir_home = os.path.dirname(os.path.dirname(os.path.dirname(__file__)))
if is_test:
cfg_file_path = os.path.join(dir_home, 'demo','demo.yaml') #'D:\Dropbox\LeafMachine2\LeafMachine2.yaml'
# cfg_file_path = 'test_installation'
cfg_testing = load_config_file_testing(dir_home, cfg_file_path)
cfg_testing['leafmachine']['project']['dir_images_local'] = os.path.join(dir_home, cfg_testing['leafmachine']['project']['dir_images_local'][0], cfg_testing['leafmachine']['project']['dir_images_local'][1])
cfg_testing['leafmachine']['project']['dir_output'] = os.path.join(dir_home, cfg_testing['leafmachine']['project']['dir_output'][0], cfg_testing['leafmachine']['project']['dir_output'][1])
last_JSON_response = voucher_vision(cfg_file_path, dir_home, cfg_testing, None)
else:
cfg_file_path = None
cfg_testing = None
last_JSON_response = voucher_vision(cfg_file_path, dir_home, cfg_testing, None)