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Datasets:
WanyueZhang
/
MulSeT

Modalities:
Image
Languages:
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Tags:
computer-vision
visual-question-answering
multi-modal
spatial-reasoning
synthetic-data
License:
Dataset card Data Studio Files
xet
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WanyueZhang commited on
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Upload dataset files (batch 56/552)

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  1. .gitattributes +251 -0
  2. train/train1059/0/0.json +0 -0
  3. train/train1059/0/0_depth_npy.npy +3 -0
  4. train/train1059/0/0_semantic_sensor_npy.npy +3 -0
  5. train/train1059/0/1.json +1063 -0
  6. train/train1059/0/1_depth_npy.npy +3 -0
  7. train/train1059/0/1_semantic_sensor_npy.npy +3 -0
  8. train/train1059/0/depth_0.png +0 -0
  9. train/train1059/0/depth_1.png +0 -0
  10. train/train1059/0/mask_questions.jsonl +5 -0
  11. train/train1059/0/questions_distance.jsonl +2 -0
  12. train/train1059/0/rgb_0.png +3 -0
  13. train/train1059/0/rgb_0_mask_Chair|4|1|1.png +3 -0
  14. train/train1059/0/rgb_0_mask_Fridge|2|1.png +3 -0
  15. train/train1059/0/rgb_1.png +3 -0
  16. train/train1059/0/rgb_1_mask_Chair|4|1|1.png +3 -0
  17. train/train1059/0/rgb_1_mask_DiningTable|4|1|0.png +3 -0
  18. train/train1059/0/rgb_1_mask_Fridge|2|1.png +3 -0
  19. train/train1059/0/semantic_0.png +0 -0
  20. train/train1059/0/semantic_1.png +0 -0
  21. train/train1059/1/0.json +0 -0
  22. train/train1059/1/0_depth_npy.npy +3 -0
  23. train/train1059/1/0_semantic_sensor_npy.npy +3 -0
  24. train/train1059/1/1.json +0 -0
  25. train/train1059/1/1_depth_npy.npy +3 -0
  26. train/train1059/1/1_semantic_sensor_npy.npy +3 -0
  27. train/train1059/1/depth_0.png +0 -0
  28. train/train1059/1/depth_1.png +0 -0
  29. train/train1059/1/mask_questions.jsonl +0 -0
  30. train/train1059/1/rgb_0.png +3 -0
  31. train/train1059/1/rgb_1.png +3 -0
  32. train/train1059/1/semantic_0.png +0 -0
  33. train/train1059/1/semantic_1.png +0 -0
  34. train/train1059/2/0.json +0 -0
  35. train/train1059/2/0_depth_npy.npy +3 -0
  36. train/train1059/2/0_semantic_sensor_npy.npy +3 -0
  37. train/train1059/2/1.json +2100 -0
  38. train/train1059/2/1_depth_npy.npy +3 -0
  39. train/train1059/2/1_semantic_sensor_npy.npy +3 -0
  40. train/train1059/2/depth_0.png +0 -0
  41. train/train1059/2/depth_1.png +0 -0
  42. train/train1059/2/mask_questions.jsonl +0 -0
  43. train/train1059/2/rgb_0.png +3 -0
  44. train/train1059/2/rgb_1.png +3 -0
  45. train/train1059/2/semantic_0.png +0 -0
  46. train/train1059/2/semantic_1.png +0 -0
  47. train/train1059/3/0.json +634 -0
  48. train/train1059/3/0_depth_npy.npy +3 -0
  49. train/train1059/3/0_semantic_sensor_npy.npy +3 -0
  50. train/train1059/3/1.json +0 -0
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train/train1059/0/mask_questions.jsonl ADDED
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1
+ {"id": 1809, "folder_dir": "train1059/0", "pair_name": "0-1:Fridge|2|1", "query": "Please combine the information from the two images and answer the following question:\nWhat is the object being masked in the second image?\nNote: The masked region is indicated by the black rectangle outlined in red in the second image.\nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Dresser\nB. Chair\nC. Fridge\nD. Drawer", "answer": "C", "object_name": "Fridge", "image_1": "train1059/0/rgb_0.png", "image_2": "train1059/0/rgb_1.png", "mask_image": "train1059/0/rgb_1_mask_Fridge|2|1.png", "options": ["Dresser", "Chair", "Fridge", "Drawer"]}
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+ {"id": 1810, "folder_dir": "train1059/0", "pair_name": "0-1:Chair|4|1|1", "query": "Please combine the information from the two images and answer the following question:\nWhat is the object being masked in the second image?\nNote: The masked region is indicated by the black rectangle outlined in red in the second image.\nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Chair\nB. DiningTable\nC. Fridge\nD. Book", "answer": "A", "object_name": "Chair", "image_1": "train1059/0/rgb_0.png", "image_2": "train1059/0/rgb_1.png", "mask_image": "train1059/0/rgb_1_mask_Chair|4|1|1.png", "options": ["Chair", "DiningTable", "Fridge", "Book"]}
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+ {"id": 1811, "folder_dir": "train1059/0", "pair_name": "0-1:DiningTable|4|1|0", "query": "Please combine the information from the two images and answer the following question:\nWhat is the object being masked in the second image?\nNote: The masked region is indicated by the black rectangle outlined in red in the second image.\nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Painting\nB. Fridge\nC. Pen\nD. DiningTable", "answer": "D", "object_name": "DiningTable", "image_1": "train1059/0/rgb_0.png", "image_2": "train1059/0/rgb_1.png", "mask_image": "train1059/0/rgb_1_mask_DiningTable|4|1|0.png", "options": ["Painting", "Fridge", "Pen", "DiningTable"]}
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+ {"id": 1812, "folder_dir": "train1059/0", "pair_name": "1-0:Fridge|2|1", "query": "Please combine the information from the two images and answer the following question:\nWhat is the object being masked in the second image?\nNote: The masked region is indicated by the black rectangle outlined in red in the second image.\nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Fridge\nB. FloorLamp\nC. Painting\nD. Chair", "answer": "A", "object_name": "Fridge", "image_1": "train1059/0/rgb_1.png", "image_2": "train1059/0/rgb_0.png", "mask_image": "train1059/0/rgb_0_mask_Fridge|2|1.png", "options": ["Fridge", "FloorLamp", "Painting", "Chair"]}
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+ {"id": 1813, "folder_dir": "train1059/0", "pair_name": "1-0:Chair|4|1|1", "query": "Please combine the information from the two images and answer the following question:\nWhat is the object being masked in the second image?\nNote: The masked region is indicated by the black rectangle outlined in red in the second image.\nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Painting\nB. Chair\nC. Painting\nD. Fridge", "answer": "B", "object_name": "Chair", "image_1": "train1059/0/rgb_1.png", "image_2": "train1059/0/rgb_0.png", "mask_image": "train1059/0/rgb_0_mask_Chair|4|1|1.png", "options": ["Painting", "Chair", "Painting", "Fridge"]}
train/train1059/0/questions_distance.jsonl ADDED
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+ {"id": 728, "folder_dir": "train1059/0", "query": "Which of the following objects is closest to Fridge in the two images? (Note: Use the distance between centroids to determine closeness.) \nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Plate\nB. Pen\nC. Vase\nD. Other\n", "answer": "A", "src_object": "Fridge", "target_object": "Plate", "question": "Which of the following objects is closest to Fridge in the two images? (Note: Use the distance between centroids to determine closeness.) \nChoose the correct option from the list below. Only respond with the corresponding letter.", "options": [{"text": "Plate", "semantic_id": "Plate|surface|4|19", "distance": 3.2752397628418777, "com": {"x": 4.8790998458862305, "y": 0.1018509715795517, "z": 6.368214130401611}}, {"text": "Pen", "semantic_id": "Pen|surface|4|25", "distance": 3.4199019474024865, "com": {"x": 4.730879783630371, "y": 0.09389401227235794, "z": 6.3627824783325195}}, {"text": "Vase", "semantic_id": "Vase|surface|4|24", "distance": 3.3688445445323785, "com": {"x": 4.7310686111450195, "y": 0.3073330521583557, "z": 6.28977108001709}}, {"text": "Other", "semantic_id": -1, "distance": -1, "com": [0, 0, 0]}], "image_1": "train1059/0/rgb_0.png", "image_2": "train1059/0/rgb_1.png"}
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+ {"id": 729, "folder_dir": "train1059/0", "query": "Which of the following objects is closest to DiningTable in the two images? (Note: Use the distance between centroids to determine closeness.) \nChoose the correct option from the list below. Only respond with the corresponding letter.\n\nA. Plate\nB. Laptop\nC. Vase\nD. Other\n", "answer": "B", "src_object": "DiningTable", "target_object": "Laptop", "question": "Which of the following objects is closest to DiningTable in the two images? (Note: Use the distance between centroids to determine closeness.) \nChoose the correct option from the list below. Only respond with the corresponding letter.", "options": [{"text": "Plate", "semantic_id": "Plate|surface|4|19", "distance": 2.7017484397998337, "com": {"x": 4.8790998458862305, "y": 0.1018509715795517, "z": 6.368214130401611}}, {"text": "Laptop", "semantic_id": "Laptop|surface|4|23", "distance": 0.4872012114058171, "com": {"x": 5.23272705078125, "y": 0.8054084777832031, "z": 3.948308229446411}}, {"text": "Vase", "semantic_id": "Vase|surface|4|24", "distance": 2.6415033172924987, "com": {"x": 4.7310686111450195, "y": 0.3073330521583557, "z": 6.28977108001709}}, {"text": "Other", "semantic_id": -1, "distance": -1, "com": [0, 0, 0]}], "image_1": "train1059/0/rgb_0.png", "image_2": "train1059/0/rgb_1.png"}
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