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Programmer-RD-AIProgrammer-RD-AI
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Merge pull request #2 from Programmer-RD-AI/deepsource-fix-4f9eedac
Remove unused imports
2 parents dc78f72 + 8bad614 commit 065ba80

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‎download.py

Lines changed: 63 additions & 55 deletions
Original file line numberDiff line numberDiff line change
@@ -1,15 +1,15 @@
1-
import pandas as pd
21
import matplotlib.pyplot as plt
3-
import numpy as np
2+
import pandas as pd
43
from tqdm import tqdm
5-
import os
4+
65
try:
76
from urllib.request import urlretrieve # Python 3
87
except ImportError:
98
from urllib import urlretrieve # Python 2
10-
classes = pd.read_csv('./classes.csv')
11-
labelnames = classes['LabelName'].tolist()
12-
classnames = classes['DisplayName'].tolist()
9+
10+
classes = pd.read_csv("./classes.csv")
11+
labelnames = classes["LabelName"].tolist()
12+
classnames = classes["DisplayName"].tolist()
1313
__imageids = []
1414
__imageids_and_bbox = {}
1515
imageids = []
@@ -24,74 +24,82 @@
2424
image_id = 0
2525

2626
imageid_and_labelname = pd.read_csv(
27-
'./open_images_data/oidv6-train-annotations-human-imagelabels.csv')
28-
imageid_and_labelname.append(pd.read_csv(
29-
'./open_images_data/test-annotations-human-imagelabels-boxable.csv'))
30-
imageid_and_labelname.append(pd.read_csv(
31-
'./open_images_data/test-annotations-machine-imagelabels.csv'))
32-
imageid_and_labelname.append(pd.read_csv(
33-
'./open_images_data/train-annotations-human-imagelabels-boxable.csv'))
34-
imageid_and_labelname.append(pd.read_csv(
35-
'./open_images_data/train-annotations-machine-imagelabels.csv'))
36-
imageid_and_labelname.append(pd.read_csv(
37-
'./open_images_data/validation-annotations-human-imagelabels-boxable.csv'))
38-
imageid_and_labelname.append(pd.read_csv(
39-
'./open_images_data/validation-annotations-machine-imagelabels.csv'))
40-
tqdm_iter = tqdm(imageid_and_labelname['ImageID'])
41-
for imageid, labelname in zip(tqdm_iter, imageid_and_labelname['LabelName']):
27+
"./open_images_data/oidv6-train-annotations-human-imagelabels.csv")
28+
imageid_and_labelname.append(
29+
pd.read_csv(
30+
"./open_images_data/test-annotations-human-imagelabels-boxable.csv"))
31+
imageid_and_labelname.append(
32+
pd.read_csv("./open_images_data/test-annotations-machine-imagelabels.csv"))
33+
imageid_and_labelname.append(
34+
pd.read_csv(
35+
"./open_images_data/train-annotations-human-imagelabels-boxable.csv"))
36+
imageid_and_labelname.append(
37+
pd.read_csv(
38+
"./open_images_data/train-annotations-machine-imagelabels.csv"))
39+
imageid_and_labelname.append(
40+
pd.read_csv(
41+
"./open_images_data/validation-annotations-human-imagelabels-boxable.csv"
42+
))
43+
imageid_and_labelname.append(
44+
pd.read_csv(
45+
"./open_images_data/validation-annotations-machine-imagelabels.csv"))
46+
tqdm_iter = tqdm(imageid_and_labelname["ImageID"])
47+
for imageid, labelname in zip(tqdm_iter, imageid_and_labelname["LabelName"]):
4248
if labelname in labelnames:
43-
tqdm_iter.set_description(f'{imageid}-{labelname}')
49+
tqdm_iter.set_description(f"{imageid}-{labelname}")
4450
__imageids.append(imageid)
4551

4652
del imageid_and_labelname
4753

48-
4954
xmin_ymin_xmax_ymax = pd.read_csv(
50-
'./open_images_data/oidv6-train-annotations-bbox.csv')
51-
xmin_ymin_xmax_ymax.append(pd.read_csv(
52-
'./open_images_data/test-annotations-bbox.csv'))
53-
xmin_ymin_xmax_ymax.append(pd.read_csv(
54-
'./open_images_data/validation-annotations-bbox.csv'))
55+
"./open_images_data/oidv6-train-annotations-bbox.csv")
56+
xmin_ymin_xmax_ymax.append(
57+
pd.read_csv("./open_images_data/test-annotations-bbox.csv"))
58+
xmin_ymin_xmax_ymax.append(
59+
pd.read_csv("./open_images_data/validation-annotations-bbox.csv"))
5560
for i in tqdm(range(len(xmin_ymin_xmax_ymax))):
5661
info = xmin_ymin_xmax_ymax.iloc[i]
57-
if info['ImageID'] in __imageids:
58-
__imageids_and_bbox[info['ImageID']] = [
59-
info['XMin'], info['YMin'], info['XMax'], info['YMax']]
62+
if info["ImageID"] in __imageids:
63+
__imageids_and_bbox[info["ImageID"]] = [
64+
info["XMin"],
65+
info["YMin"],
66+
info["XMax"],
67+
info["YMax"],
68+
]
6069
del xmin_ymin_xmax_ymax
6170

6271
urls = pd.read_csv(
63-
'./open_images_data/oidv6-train-images-with-labels-with-rotation.csv')
64-
urls.append(pd.read_csv(
65-
'./open_images_data/test-images-with-rotation.csv'))
66-
urls.append(pd.read_csv(
67-
'./open_images_data/train-images-boxable-with-rotation.csv'))
68-
urls.append(pd.read_csv(
69-
'./open_images_data/validation-images-with-rotation.csv'))
72+
"./open_images_data/oidv6-train-images-with-labels-with-rotation.csv")
73+
urls.append(pd.read_csv("./open_images_data/test-images-with-rotation.csv"))
74+
urls.append(
75+
pd.read_csv("./open_images_data/train-images-boxable-with-rotation.csv"))
76+
urls.append(
77+
pd.read_csv("./open_images_data/validation-images-with-rotation.csv"))
7078
for i in tqdm(range(len(urls))):
7179
url = urls.iloc[i]
72-
if url['ImageID'] in __imageids:
73-
urlretrieve(url['OriginalURL'], f"./data/{image_id}.png")
74-
xmin, ymin, xmax, ymax = __imageids_and_bbox[url['ImageID']]
80+
if url["ImageID"] in __imageids:
81+
urlretrieve(url["OriginalURL"], f"./data/{image_id}.png")
82+
xmin, ymin, xmax, ymax = __imageids_and_bbox[url["ImageID"]]
7583
file_names.append(f"./data/{image_id}.png")
76-
type_of_data.append(url['Subset'])
77-
imageurls.append(url['OriginalURL'])
78-
imageurls_original.append(url['OriginalLandingURL'])
79-
imageids.append(url['ImageID'])
84+
type_of_data.append(url["Subset"])
85+
imageurls.append(url["OriginalURL"])
86+
imageurls_original.append(url["OriginalLandingURL"])
87+
imageids.append(url["ImageID"])
8088
xmins.append(xmin)
8189
ymins.append(ymin)
8290
xmaxs.append(xmax)
8391
ymaxs.append(ymax)
8492
image_id += 1
8593

8694
data = pd.DataFrame({
87-
'ImageIds': imageids,
88-
'XMin': xmins,
89-
'YMin': ymins,
90-
'XMax': xmaxs,
91-
'YMax': ymaxs,
92-
'File Name': file_names,
93-
'ImageUrls': imageurls,
94-
'Og_ImageUrls': imageurls_original,
95-
'Type of Data': type_of_data,
95+
"ImageIds": imageids,
96+
"XMin": xmins,
97+
"YMin": ymins,
98+
"XMax": xmaxs,
99+
"YMax": ymaxs,
100+
"File Name": file_names,
101+
"ImageUrls": imageurls,
102+
"Og_ImageUrls": imageurls_original,
103+
"Type of Data": type_of_data,
96104
})
97-
data.to_csv('./data.csv')
105+
data.to_csv("./data.csv")

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