Datasets:
Formats:
webdataset
Size:
1M - 10M
Tags:
sgt
semantic-generative-tuning
unified-multimodal
image-segmentation
visual-understanding
visual-generation
License:
Delete sam_selection
Browse filesThis view is limited to 50 files because it contains too many changes. See raw diff
- sam_selection/detar.py +0 -33
- sam_selection/read_filename.py +0 -22
- sam_selection/sa_10004.json +0 -1
- sam_selection/sa_10064.json +0 -1
- sam_selection/sa_10079.json +0 -1
- sam_selection/sa_10150.json +0 -1
- sam_selection/sa_10214896.json +0 -1
- sam_selection/sa_10214911.json +0 -1
- sam_selection/sa_10215292.json +0 -1
- sam_selection/sa_10215304.json +0 -1
- sam_selection/sa_10215568.json +0 -1
- sam_selection/sa_10215706.json +0 -1
- sam_selection/sa_10215719.json +0 -1
- sam_selection/sa_10215740.json +0 -1
- sam_selection/sa_10215790.json +0 -1
- sam_selection/sa_10215891.json +0 -1
- sam_selection/sa_10215999.json +0 -1
- sam_selection/sa_10216039.json +0 -1
- sam_selection/sa_10216252.json +0 -1
- sam_selection/sa_10216264.json +0 -1
- sam_selection/sa_10216400.json +0 -1
- sam_selection/sa_10216567.json +0 -1
- sam_selection/sa_10216833.json +0 -1
- sam_selection/sa_10216877.json +0 -1
- sam_selection/sa_10217016.json +0 -1
- sam_selection/sa_10217024.json +0 -1
- sam_selection/sa_10217026.json +0 -1
- sam_selection/sa_10217029.json +0 -1
- sam_selection/sa_10217055.json +0 -1
- sam_selection/sa_10217105.json +0 -1
- sam_selection/sa_10217111.json +0 -1
- sam_selection/sa_10217125.json +0 -1
- sam_selection/sa_10217287.json +0 -1
- sam_selection/sa_10217508.json +0 -1
- sam_selection/sa_10217516.json +0 -1
- sam_selection/sa_10217657.json +0 -1
- sam_selection/sa_10217732.json +0 -1
- sam_selection/sa_10217763.json +0 -1
- sam_selection/sa_10217793.json +0 -1
- sam_selection/sa_10217984.json +0 -1
- sam_selection/sa_10217997.json +0 -1
- sam_selection/sa_10218096.json +0 -1
- sam_selection/sa_10218117.json +0 -1
- sam_selection/sa_10218174.json +0 -1
- sam_selection/sa_10218181.json +0 -1
- sam_selection/sa_10218273.json +0 -1
- sam_selection/sa_10218331.json +0 -1
- sam_selection/sa_10218364.json +0 -1
- sam_selection/sa_10218387.json +0 -1
- sam_selection/sa_10218465.json +0 -1
sam_selection/detar.py
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import os
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os.chdir('/workspace/public_datasets/sam_selection/')
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import tarfile
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from tqdm import tqdm
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def extract_tar_files(tar_file_list, output_directory):
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# 读取 tar_file.txt 文件，获取所有 .tar 文件名
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with open(tar_file_list, 'r') as f:
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tar_files = f.read().splitlines()
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# 确保输出目录存在
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if not os.path.exists(output_directory):
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os.makedirs(output_directory)
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# 遍历每个 .tar 文件并解压
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for tar_file in tqdm(tar_files, desc="Extracting files", unit="file"):
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tar_path = os.path.join(os.path.dirname(tar_file_list), tar_file)
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if os.path.exists(tar_path):
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with tarfile.open(tar_path, 'r') as tar:
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members = tar.getmembers()
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for member in tqdm(members, desc=f"Extracting {tar_file}", unit="file", leave=False):
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tar.extract(member, path=output_directory)
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else:
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print(f"Warning: File {tar_file} does not exist.")
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# 指定 tar_file.txt 文件路径和输出目录
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tar_file_list = 'tar_file.txt'
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output_directory = '/group/40033/public_datasets/sam_selection/'
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# 调用函数
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extract_tar_files(tar_file_list, output_directory)
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print("所有文件已解压完成。")
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sam_selection/read_filename.py
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import os
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def list_tar_files(directory, output_file):
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# 获取指定目录下的所有文件和文件夹
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files = os.listdir(directory)
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# 过滤出以 .tar 结尾的文件
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tar_files = [file for file in files if file.endswith('.tar')]
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# 将文件名写入输出文件
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with open(output_file, 'w') as f:
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for tar_file in tar_files:
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f.write(tar_file + '\n')
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# 指定目录和输出文件
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directory = '/group/40033/public_datasets/sam_selection/' # 替换为你的目录路径
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output_file = 'tar_file.txt'
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# 调用函数
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list_tar_files(directory, output_file)
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print(f"所有 .tar 文件名已写入 {output_file}")
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sam_selection/sa_10004.json
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{"image": {"image_id": 10004, "width": 2000, "height": 1500, "file_name": "sa_10004.jpg"}, "annotations": [{"bbox": [832.0, 1367.0, 108.0, 77.0], "area": 3341, "segmentation": {"size": [1500, 2000], "counts": "\\TTV17`^18K4L4M4M2M2O2N1O1O1O00000000000O100000O1000O100O01O10O01O00001O00001O00010O0010O01O01O01O010O001O01O01O010O00010O01O010O0010O00010O01O000010O0001O01O01O010O001O010O0001O00100O1O1O1O100O101N1O2O0O2N1O1N3N1N3M3N2M2O4Kem]`1"}, "predicted_iou": 0.9341139793395996, "point_coords": [[911.75, 1393.6875]], "crop_box": [436.0, 933.0, 692.0, 567.0], "id": 228922350, "stability_score": 0.9690994620323181}, {"bbox": [1419.0, 1099.0, 100.0, 123.0], "area": 3642, "segmentation": {"size": [1500, 2000], "counts": "WfoP29`^16L4L3M4L3N1O2N1N3N1O2N1O1O1O1O2N100O2O01O010O1O1O1O1O101N1O001O01O01O0000010N11O0000000001O0001O000001O0000001O01O000000001O01O01O000000000000001N11O000O10001O0000001N1000O10O2M2N2N3L3M3N2N3N1N3M2N2M_nme0"}, "predicted_iou": 0.890169084072113, "point_coords": [[1437.75, 1110.1875]], "crop_box": [1308.0, 933.0, 692.0, 567.0], "id": 228922351, "stability_score": 0.9609585404396057}, {"bbox": [1530.0, 129.0, 256.0, 132.0], "area": 21178, "segmentation": {"size": [1500, 2000], "counts": "[]QV23d^19J2O1N200O10000O100O10000O10000000O0100000000O1000000O1000O10O1O100O100N3K4N2O1O1O1O2N102M6J4M2M2O1O001N101O0O100O100O2O000O100O10001N10000O100O1000000O2O0O10000O2O0O2N1N3M2M4K4O1O2N1O101O0O2O0O2O1N2N2O1O1O1O001O1O1O001O001O0O101O0O100O2O0O101N1O101N1000000O10001O0000001N100O100O1O1O010000000001O10O01O1O001O00001O000000000000000000000O2O0O101N100O2O000O10001O0000000O1000001N1000001N10000O2O0O1O100O1O10000O2O001O001O001O001O1O0000001O0O101O1O2N2N1O2N1O1N2aNmcN3S\\1LocN3Q\\1LQdN3o[1MRdN2n[1MSdN3m[1LUdN2m[1MSdN3o[1KQdN5P\\1IQdN6R\\1HocNIJ_O[\\1f0kcNHf\\15[cNIi\\15WcNJl\\14TcNLn\\12RcNMR]10obNOV]1JlbN6m]10001O0O101N11O01N5Ifig9"}, "predicted_iou": 0.9559609889984131, "point_coords": [[1697.25, 248.0625]], "crop_box": [1308.0, 0.0, 692.0, 567.0], "id": 228922352, "stability_score": 0.9578499794006348}, {"bbox": [1098.0, 1002.0, 169.0, 87.0], "area": 9312, "segmentation": {"size": [1500, 2000], "counts": "\\]Yb15e^14L3N2O1N2O1N1N3J6L4N2M3N1O2N1O2O0O10001O000O20O00000001O00000010O0001O00001O00001O001O001O001O0O2O001O0O101N100O1O1O2N1O1O100O1O1O2O0O1O1O1O100O100000000O11N10000001O00000001O000010O00010O01O010O100O1O010O010O01O010O001O0000001O010O0000010O0001O001O001O1O001O0O2O1O001N3N2N6J1N2O1O0O2O1N2O0O2N2O0O2O001O0O2O1O001O1O0O3N1N4L2O1N2N3M2N2M3M\\W_Q1"}, "predicted_iou": 0.9442909955978394, "point_coords": [[1174.75, 1039.3125]], "crop_box": [872.0, 933.0, 692.0, 567.0], "id": 228922353, "stability_score": 0.9640219211578369}, {"bbox": [1285.0, 111.0, 231.0, 130.0], "area": 16948, "segmentation": {"size": [1500, 2000], "counts": 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sam_selection/sa_10079.json
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sam_selection/sa_10150.json
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sam_selection/sa_10214896.json
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sam_selection/sa_10214911.json
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{"image": {"image_id": 10214911, "width": 2250, "height": 1500, "file_name": "sa_10214911.jpg"}, "annotations": [{"bbox": [1440.0, 531.0, 169.0, 320.0], "area": 24115, "segmentation": {"size": [1500, 2250], "counts": "PomQ2m0k]1a0QOg0_Oa0D=F8J5J6K5L3L4L4M4L3M3M3M4L4L3M4L4L3M4M3L4L3N2M3N3M2M4M2M3N2N2M3N2M4M2N2N3L3N2N3M2M3N2N3M2N3M2N2N2OO00000O1N2nNWiNoIkV1k5hiNeI\\V1T6Y1H8M3M4M2O1N3N1O2N1N2O2N1O2O1N2N1O2N2N101N2O001N2O1O1N2O1O1O1O2N1O2N1O2N1O2OO0101N10000O101O0O100O10001O002N1O010O1000O1O1O10O00100O3M2N2O1N1000103K2N2O2M4M4O2L2N112L2O1O1M3O3N1K6J5K8H6O1N3L3K4K7I;E9F<B?NEe0[O3040J6I8I2MceXm0"}, "predicted_iou": 0.8837544322013855, "point_coords": [[1516.34375, 660.1875]], "crop_box": [869.0, 0.0, 1381.0, 1006.0], "id": 402428554, "stability_score": 0.9674209952354431}, {"bbox": [1498, 699, 308, 800], "area": 76888, "segmentation": {"size": [1500, 2250], "counts": "PRcT2b0o]1>\\bNUOn\\1R1kbNTOj\\1f1J5M3L;E4L5L9H4K4M4K4M4K4L:F3M4L4K7J5L2M3N4L6J3L4M1O3M3M4L3M1O3M3M8H3M2N2O3L5K4L4M1N4L4M3L4N0O1O2N3L5L3M2N3M2N2N3N10O11N2N3M2M2N3L4M4L2N1O3M4L3M2O2O1O1N3M010O0020001L3N3N2N2M2M5J3M2M6K4L3NSEYlNe:PT12N5K3N3M4OL6LO0O5N3M03J4NN304LO3K3M22N1001N20N200O00O1N30M3M4M11L4OO6H5L11N2O0001O5I21N2OO4M2N2O2NO02L:H2M7LM21M:E4M3ON2N03L;G4L3LO3L3M2N2M4L3M3M2N3M4L4M3L3M3M5K4K4M3M3M3L6L4K4L4L3M4L3M4L2N2N4L4L4L3M2N4L4L4L3M2N3M4L3M4L3M3M3M3M3M3M2M4M3M3M3N1N2N4L4K4M2N2N5K3M4L8H4L3N3L1N10001O2N3M3N2M2N3M3M3M3L3N2N3M4M3L3M2N3M4L3M2M3N2N3M5K4L4L3M2N2N2N2N1O4L3M2N2N2N3M3M4L3M1O2N3M4L4L2N2N2N3M3M4L2N2N2N5K3M2N2N3M2N2N1O1N5L3M2N3M2N1O1O5JP_Wd0"}, "predicted_iou": 0.899807870388031, "point_coords": [[1602.65625, 965.5625]], "crop_box": [869.0, 494.0, 1381.0, 1006.0], "id": 402428555, "stability_score": 0.9566574692726135}, {"bbox": [1440, 531, 367, 968], "area": 103004, "segmentation": {"size": [1500, 2250], "counts": "QomQ2i0n]1a0TOi0ZOc0C<H7I6K5J5L5L3L5L3M3M2N4L4L4L4L3M4L3M4L4M3L3M3N2M4M2M3N3M1N3N2N2M3N3M2M3N3M2M4M3M2M3N2N3M2N2N2N3N2M3M3M3M2O2M2N3M3M2O2M3M3N2M2N3N2M3M4M3L4L4M2M3N2N3L3N3M3M2N2N3M2M2O2N2N2N3M2O1N2N2N3N1N2O1N3M4M1N2N3N2M2M3N3N1O2M3M1O3M3N1N2N2O2M4N1N002M3M3N2M3N101N20O01N2N1O3N10O100O002O103M0O2N2O2N10N01O1O5J3N2N3L5M3L4K3O002M6J5L3M1N1100N01O0011OO2O1N1O1O1N31N010OO010O1001O1M12N11N4L003M012M1O2NO1011N1O0O013M2N2O2L3N2N3M9G3M3L104K2O4M4KO07J2N5K1OM2M3N3L4M2M3M3M3M3M4L3M4L3M4L4L3M5K3M3M4L4L4L3M4L5K4L3M2N3M4L4L3M4L3M3M4L4L3M3M3M4L3M4L3L4M3M3M3M3M3M2N3M4L3M3M2N3M3M3M3M3M2N4L3M3M3M2N3M2N3M3M3M3M2N3M3M2N3M3M3M3M3M3M3M3M3M3M3M3M3M2N3M2N3M3M2N3M3M3M2N2N3M3M2N2N3M4L3M3M3M3M3M3M3M2N2N3M2N4L2N4L2N3M2N3M3M3M2N2N4L3M2N2N3M2N2N2N1O3M3M2N2N3M2N3L3N3LUPVd0"}, "predicted_iou": 1.0254573822021484, "point_coords": [[1516.34375, 839.8125]], "crop_box": [869.0, 494.0, 1381.0, 1006.0], "id": 402428556, "stability_score": 0.9863783717155457}]}
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sam_selection/sa_10215292.json
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sam_selection/sa_10215304.json
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sam_selection/sa_10215719.json
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sam_selection/sa_10215740.json
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sam_selection/sa_10215790.json
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sam_selection/sa_10216252.json
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sam_selection/sa_10216264.json
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sam_selection/sa_10216400.json
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sam_selection/sa_10217029.json
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sam_selection/sa_10217055.json
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sam_selection/sa_10217105.json
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sam_selection/sa_10217111.json
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sam_selection/sa_10217287.json
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sam_selection/sa_10217732.json
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sam_selection/sa_10217763.json
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sam_selection/sa_10217793.json
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sam_selection/sa_10217984.json
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sam_selection/sa_10218117.json
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sam_selection/sa_10218174.json
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sam_selection/sa_10218181.json
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sam_selection/sa_10218273.json
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sam_selection/sa_10218331.json
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