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from os import listdir, walk
from os.path import isfile, isdir, join, splitext, exists, getmtime
from random import seed, randint, choice
import re
import json
import datetime
import argparse
parser = argparse.ArgumentParser(description='Generate BBBicycles split.')
parser.add_argument('-p', '--path', type=str, required=True,
help='directory containing the ID folders')
args = parser.parse_args()
path = args.path
random_seed = seed(1337)
train_val_bike_type_split = 10
img_regex = re.compile('(^img.\d*[.]png$)')
dir_regex = re.compile('(^\w+_)')
train = open("bike_train.txt", "w")
query_v = open("bike_query_val.txt", "w")
galley_v = open("bike_gallery_val.txt", "w")
query_t = open("bike_query_test.txt", "w")
galley_t = open("bike_gallery_test.txt", "w")
num_ids = 0
num_imgs = 0
num_damaged_imgs = 0
num_broken_imgs = 0
num_bent_imgs = 0
num_missingpart_imgs = 0
nums_missingpart_imgs = [0 for i in range(5)]
models_dist = {}
num_train_ids = 0
num_train_imgs = 0
num_damaged_train_imgs = 0
num_broken_train_imgs = 0
num_bent_train_imgs = 0
num_missingpart_train_imgs = 0
nums_missingpart_train_imgs = [0 for i in range(5)]
models_dist_train = {}
num_val_ids = 0
num_val_imgs = 0
num_damaged_val_imgs = 0
num_broken_val_imgs = 0
num_bent_val_imgs = 0
num_missingpart_val_imgs = 0
nums_missingpart_val_imgs = [0 for i in range(5)]
models_dist_val = {}
num_test_ids = 0
num_test_imgs = 0
num_damaged_test_imgs = 0
num_broken_test_imgs = 0
num_bent_test_imgs = 0
num_missingpart_test_imgs = 0
nums_missingpart_test_imgs = [0 for i in range(5)]
models_dist_test = {}
for id, bike in enumerate(listdir(path)):
if isdir(join(path, bike)) and dir_regex.match(bike) and exists(join(path, bike, "before")) and len(listdir(join(path, bike, "before"))) != 0 and exists(join(path, bike, "after")) and len(listdir(join(path, bike, "after"))) != 0 and exists(join(path, bike, "fixed_data.json")):
#aggiungere: prendere json dell'identità per estrarre info
json_fixed = open(join(path, bike, 'fixed_data.json'),)
data_fixed = json.load(json_fixed)
if str(data_fixed['Bike Type']) not in models_dist:
models_dist[str(data_fixed['Bike Type'])] = {str(data_fixed['Model']): 1}
elif str(data_fixed['Model']) not in models_dist[str(data_fixed['Bike Type'])]:
models_dist[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = 1
else:
models_dist[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = models_dist[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] + 1
c=0
num_ids = num_ids + 1
for type in ["before", "after"]:
for file in listdir(join(path, bike, type)):
if img_regex.match(file):
if exists(join(path, bike, type, splitext(file)[0] + '_variable.json')):
json_var = open(join(path, bike, type, splitext(file)[0] + '_variable.json'),)
data = json.load(json_var)
dmgid = 0 if type == "before" else int(data["Damage Type"])
missid = "00000" if type == "before" else str(data["Removed Parts"])
json_var.close()
if dmgid != 0:
num_damaged_imgs = num_damaged_imgs + 1
if dmgid == 2 or dmgid == 3:
num_broken_imgs = num_broken_imgs + 1
if dmgid == 1 or dmgid == 3:
num_bent_imgs = num_bent_imgs + 1
if missid != "00000" :
num_missingpart_imgs = num_missingpart_imgs + 1
for i in range(5):
if missid[i] == "1":
nums_missingpart_imgs[i] = nums_missingpart_imgs[i] + 1
num_imgs = num_imgs + 1
c=c+1
else:
print(bike)
if c != 14:
print(bike)
if str(data_fixed['Model']) in ['mfactory ', 'ghost', 'oldbike', 'rondo', 'verdona']:
#Train
if str(data_fixed['Bike Type']) not in models_dist_train:
models_dist_train[str(data_fixed['Bike Type'])] = {str(data_fixed['Model']): 1}
elif str(data_fixed['Model']) not in models_dist_train[str(data_fixed['Bike Type'])]:
models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = 1
else:
models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] + 1
num_train_ids = num_train_ids + 1
for type in ["before", "after"]:
for file in listdir(join(path, bike, type)):
if img_regex.match(file) and exists(join(path, bike, type, splitext(file)[0] + '_variable.json')):
img_path = join(bike, type, file)
json_var = open(join(path, bike, type, splitext(file)[0] + '_variable.json'),)
data = json.load(json_var)
camid = int(data["Focal Length"])
viewid = int(data["Viewing Side"])
dmgid = 0 if type == "before" else int(data["Damage Type"])
missid = "00000" if type == "before" else str(data["Removed Parts"])
train.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
json_var.close()
if dmgid != 0:
num_damaged_train_imgs = num_damaged_train_imgs + 1
if dmgid == 2 or dmgid == 3:
num_broken_train_imgs = num_broken_train_imgs + 1
if dmgid == 1 or dmgid == 3:
num_bent_train_imgs = num_bent_train_imgs + 1
if missid != "00000" :
num_missingpart_train_imgs = num_missingpart_train_imgs + 1
for i in range(5):
if missid[i] == "1":
nums_missingpart_train_imgs[i] = nums_missingpart_train_imgs[i] + 1
num_train_imgs = num_train_imgs + 1
else:
if str(data_fixed['Model']) not in ['mirage', 'gbike', 'enduro']:
if str(data_fixed['Model']) not in ['becane', 'btwin', 'croad'] and randint(0, 100) > train_val_bike_type_split:
if str(data_fixed['Bike Type']) not in models_dist_train:
models_dist_train[str(data_fixed['Bike Type'])] = {str(data_fixed['Model']): 1}
elif str(data_fixed['Model']) not in models_dist_train[str(data_fixed['Bike Type'])]:
models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = 1
else:
models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = models_dist_train[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] + 1
num_train_ids = num_train_ids + 1
for type in ["before", "after"]:
for file in listdir(join(path, bike, type)):
if img_regex.match(file) and exists(join(path, bike, type, splitext(file)[0] + '_variable.json')):
img_path = join(bike, type, file)
json_var = open(join(path, bike, type, splitext(file)[0] + '_variable.json'),)
data = json.load(json_var)
camid = int(data["Focal Length"])
viewid = int(data["Viewing Side"])
dmgid = 0 if type == "before" else int(data["Damage Type"])
missid = "00000" if type == "before" else str(data["Removed Parts"])
train.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
json_var.close()
if dmgid != 0:
num_damaged_train_imgs = num_damaged_train_imgs + 1
if dmgid == 2 or dmgid == 3:
num_broken_train_imgs = num_broken_train_imgs + 1
if dmgid == 1 or dmgid == 3:
num_bent_train_imgs = num_bent_train_imgs + 1
if missid != "00000" :
num_missingpart_train_imgs = num_missingpart_train_imgs + 1
for i in range(5):
if missid[i] == "1":
nums_missingpart_train_imgs[i] = nums_missingpart_train_imgs[i] + 1
num_train_imgs = num_train_imgs + 1
else:
#Val
if str(data_fixed['Bike Type']) not in models_dist_val:
models_dist_val[str(data_fixed['Bike Type'])] = {str(data_fixed['Model']): 1}
elif str(data_fixed['Model']) not in models_dist_val[str(data_fixed['Bike Type'])]:
models_dist_val[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = 1
else:
models_dist_val[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = models_dist_val[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] + 1
num_val_ids = num_val_ids + 1
for type in ["before", "after"]:
files = [f for f in listdir(join(path, bike, type)) if img_regex.match(f) and exists(join(path, bike, type, splitext(f)[0] + '_variable.json'))]
file = choice(files)
img_path = join(bike, type, file)
json_var = open(join(path, bike, type, splitext(file)[0] + '_variable.json'),)
data = json.load(json_var)
camid = int(data["Focal Length"])
viewid = int(data["Viewing Side"])
dmgid = 0 if type == "before" else int(data["Damage Type"])
missid = "00000" if type == "before" else str(data["Removed Parts"])
if type == "before" :
galley_v.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
else:
query_v.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
json_var.close()
if dmgid != 0:
num_damaged_val_imgs = num_damaged_val_imgs + 1
if dmgid == 2 or dmgid == 3:
num_broken_val_imgs = num_broken_val_imgs + 1
if dmgid == 1 or dmgid == 3:
num_bent_val_imgs = num_bent_val_imgs + 1
if missid != "00000" :
num_missingpart_val_imgs = num_missingpart_val_imgs + 1
for i in range(5):
if missid[i] == "1":
nums_missingpart_val_imgs[i] = nums_missingpart_val_imgs[i] + 1
num_val_imgs = num_val_imgs + 1
else:
#Test
if str(data_fixed['Bike Type']) not in models_dist_test:
models_dist_test[str(data_fixed['Bike Type'])] = {str(data_fixed['Model']): 1}
elif str(data_fixed['Model']) not in models_dist_test[str(data_fixed['Bike Type'])]:
models_dist_test[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = 1
else:
models_dist_test[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] = models_dist_test[str(data_fixed['Bike Type'])][str(data_fixed['Model'])] + 1
num_test_ids = num_test_ids + 1
for type in ["before", "after"]:
files = [f for f in listdir(join(path, bike, type)) if img_regex.match(f) and exists(join(path, bike, type, splitext(f)[0] + '_variable.json'))]
if not files:
print(join(path, bike, type))
file = choice(files)
img_path = join(bike, type, file)
json_var = open(join(path, bike, type, splitext(file)[0] + '_variable.json'),)
data = json.load(json_var)
camid = int(data["Focal Length"])
viewid = int(data["Viewing Side"])
dmgid = 0 if type == "before" else int(data["Damage Type"])
missid = "00000" if type == "before" else str(data["Removed Parts"])
if type == "before" :
galley_t.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
else:
query_t.write("{} {} {} {} {} {}\n".format(img_path, id, camid, viewid, dmgid, missid))
json_var.close()
if dmgid != 0:
num_damaged_test_imgs = num_damaged_test_imgs + 1
if dmgid == 2 or dmgid == 3:
num_broken_test_imgs = num_broken_test_imgs + 1
if dmgid == 1 or dmgid == 3:
num_bent_test_imgs = num_bent_test_imgs + 1
if missid != "00000" :
num_missingpart_test_imgs = num_missingpart_test_imgs + 1
for i in range(5):
if missid[i] == "1":
nums_missingpart_test_imgs[i] = nums_missingpart_test_imgs[i] + 1
num_test_imgs = num_test_imgs + 1
json_fixed.close()
else:
print(bike)
train.close()
query_v.close()
galley_v.close()
query_t.close()
galley_t.close()
data = {}
data["General"] = []
data["General"].append({
'Num IDs': num_ids,
'Num Bike types': len(models_dist.keys()),
'Num Models': sum(len(models_dist[k].keys()) for k in models_dist.keys()),
'Num images': num_imgs,
'Num bent images': num_bent_imgs,
'Num broken images': num_broken_imgs,
'Num damaged images': num_damaged_imgs,
'Num images with missing parts': num_missingpart_imgs,
'Num images with missing Front Wheel': nums_missingpart_imgs[0],
'Num images with missing Rear Wheel': nums_missingpart_imgs[1],
'Num images with missing Seat': nums_missingpart_imgs[2],
'Num images with missing Handlebar': nums_missingpart_imgs[3],
'Num images with missing Pedals': nums_missingpart_imgs[4]
})
data["Train"] = []
data["Train"].append({
'Num IDs': num_train_ids,
'Num Bike types': len(models_dist_train.keys()),
'Num Models': sum(len(models_dist_train[k].keys()) for k in models_dist_train.keys()),
'Num images': num_train_imgs,
'Num bent images': num_bent_train_imgs,
'Num broken images': num_broken_train_imgs,
'Num damaged images': num_damaged_train_imgs,
'Num images with missing parts': num_missingpart_train_imgs,
'Num images with missing Front Wheel': nums_missingpart_train_imgs[0],
'Num images with missing Rear Wheel': nums_missingpart_train_imgs[1],
'Num images with missing Seat': nums_missingpart_train_imgs[2],
'Num images with missing Handlebar': nums_missingpart_train_imgs[3],
'Num images with missing Pedals': nums_missingpart_train_imgs[4]
})
data["Validation"] = []
data["Validation"].append({
'Num IDs': num_val_ids,
'Num Bike types': len(models_dist_val.keys()),
'Num Models': sum(len(models_dist_val[k].keys()) for k in models_dist_val.keys()),
'Num images': num_val_imgs,
'Num bent images': num_bent_val_imgs,
'Num broken images': num_broken_val_imgs,
'Num damaged images': num_damaged_val_imgs,
'Num images with missing parts': num_missingpart_val_imgs,
'Num images with missing Front Wheel': nums_missingpart_val_imgs[0],
'Num images with missing Rear Wheel': nums_missingpart_val_imgs[1],
'Num images with missing Seat': nums_missingpart_val_imgs[2],
'Num images with missing Handlebar': nums_missingpart_val_imgs[3],
'Num images with missing Pedals': nums_missingpart_val_imgs[4]
})
data["Test"] = []
data["Test"].append({
'Num IDs': num_test_ids,
'Num Bike types': len(models_dist_test.keys()),
'Num Models': sum(len(models_dist_test[k].keys()) for k in models_dist_test.keys()),
'Num images': num_test_imgs,
'Num bent images': num_bent_test_imgs,
'Num broken images': num_broken_test_imgs,
'Num damaged images': num_damaged_test_imgs,
'Num images with missing parts': num_missingpart_test_imgs,
'Num images with missing Front Wheel': nums_missingpart_test_imgs[0],
'Num images with missing Rear Wheel': nums_missingpart_test_imgs[1],
'Num images with missing Seat': nums_missingpart_test_imgs[2],
'Num images with missing Handlebar': nums_missingpart_test_imgs[3],
'Num images with missing Pedals': nums_missingpart_test_imgs[4]
})
with open('bike_current_split_stats.json', 'w', encoding='utf-8') as f:
json.dump(data, f, ensure_ascii=False, indent=4)
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