index int64 2 3M | question stringclasses 377
values | hint stringclasses 97
values | answer stringclasses 4
values | A stringlengths 1 460 | B stringlengths 1 460 | C stringlengths 1 460 | D stringlengths 1 460 | category stringclasses 20
values | image imagewidth (px) 55 512 | source stringclasses 563
values | L2-category stringclasses 6
values | comment stringclasses 177
values | split stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
1,857 | What direction is China in Mongolia? | nan | B | east | south | west | north | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev | |
1,001,680 | Which Python code can generate the content of the image? | nan | B | def get_vowels(string):
return [vowel for vowel in string if vowel in 'aeiou']
print("Vowels are:", get_vowels('string')) | def get_vowels(string):
return [vowel for vowel in string if vowel in 'aeiou']
print("Vowels are:", get_vowels('This is some random string')) | def get_vowels(string):
return [vowel for vowel in string if vowel in 'weiou']
print("Vowels are:", get_vowels('This is some random string')) | def get_vowels(string):
return [vowel for vowel in string if vowel in 'aeiou']
print("Vowels are:", get_vowels('This is a string')) | structuralized_imagetext_understanding | https://zhuanlan.zhihu.com/p/374461054 | logic_reasoning | nan | dev | |
1,001,615 | Which category does this image belong to? | nan | D | abstract painting | MRI image | icon | microscopic image | image_style | https://visualsonline.cancer.gov/retrieve.cfm?imageid=2129&dpi=300&fileformat=jpg | coarse_perception | nan | dev | |
3,000,659 | How many giraffes are in this photo? | nan | D | two | four | zero | one | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000000870.jpg | dev | |
2,001,156 | What can be the relationship between the two persons in this image? | nan | D | Brother and sister | Husband and wife | Father and daughter | Mother and son | social_relation | relation_reasoning | nan | dev | ||
1,001,532 | what direction is the person facing? | nan | B | right | front | back | left | object_localization | finegrained_perception (instance-level) | nan | dev | ||
1,000,474 | Which of the following statements describess living in an independent city-state? | Athens was one of the most powerful independent city-states in ancient Greece. Look at the definitions below. Then answer the question. | C | I live by myself in the wilderness. | I vote for a president that rules over many different cities. | My city rules itself and is not part of a larger country. | All the decisions about my city are made by a faraway emperor. | structuralized_imagetext_understanding | scienceqa | logic_reasoning | nan | dev | |
2,001,575 | Which category does this image belong to? | nan | D | digital art | photo | oil painting | sketch | image_style | https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcRen8j7eNMsWB1b8syLd2qgjAaI-DDnqZGK7A&usqp=CAU | coarse_perception | nan | dev | |
3,001,061 | What kind of weather is depicted in the picture? | nan | C | rainy | windy | snowy | sunny | image_scene | coarse_perception | nan | dev | ||
1,001,672 | Which Python code can generate the content of the image? | nan | B | import re
result = re.match(r'(\w+)=(\d+)', 'set width=20 and height=10')
print(result) | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=20 and height=10')
print(result) | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=30 and height=10')
print(result) | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=20 and height=15')
print(result) | structuralized_imagetext_understanding | https://www.runoob.com/python/python-reg-expressions.html | logic_reasoning | nan | dev | |
1,001,346 | Which mood does this image convey? | nan | B | Angry | Sad | Anxious | Happy | image_emotion | coarse_perception | nan | dev | ||
3,001,791 | Which of the following captions best describes this image? | nan | B | A group of people walking across a bridge | A person sitting on a rock near a river | A woman standing on a balcony overlooking a city | A couple sitting on a bench in a park | image_scene | coarse_perception | nan | dev | ||
1,666 | Which Python code can generate the content of the image? | nan | A | print str
print str[0]
print str[2:5]
print str[2:]
print str * 2
print str + "TEST" | print str
print str[1]
print str[2:5]
print str[2:]
print str * 2
print str + "TEST" | print str
print str[0]
print str[1:5]
print str[2:]
print str * 2
print str + "TEST" | print str
print str[0]
print str[2:5]
print str[3:]
print str * 2
print str + "TEST" | structuralized_imagetext_understanding | https://www.runoob.com/python/python-variable-types.html | logic_reasoning | nan | dev | |
2,001,975 | In nature, what's the relationship between these two creatures? | nan | D | Parasitic relationships | Symbiotic relationship | Predatory relationships | Competitive relationships | nature_relation | https://th.bing.com/th/id/R.dab6202087c3a0c0c2fd33c6aae82b13?rik=UftKuyST4oWmng&riu=http%3a%2f%2f5b0988e595225.cdn.sohucs.com%2fimages%2f20200210%2f70f5518982644814a95d5c9702608072.JPG&ehk=JrwicqBrsDz0JMGVYN8ydKVn68JxoiL2Caujb6fvQIA%3d&risl=&pid=ImgRaw&r=0 | relation_reasoning | nan | dev | |
1,001,602 | what style is depicted in this image? | nan | D | dadaism | impressionism | post-Impressionism | modernism | image_style | coarse_perception | nan | dev | ||
1,305 | what is the color of this object? | nan | B | red | blue | yellow | green | attribute_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,001,561 | The object shown in this figure: | nan | D | Is commonly used in many industrial applications, including electronics and optics | Is a mineral that occurs in many different forms and colors | Has a high melting point of around 1,650°C | All of these options are correct. | physical_property_reasoning | https://bkimg.cdn.bcebos.com/pic/f3d3572c11dfa9ecc9c0b89869d0f703908fc157 | attribute_reasoning | nan | dev | |
1,550 | The object shown in this figure: | nan | A | Is a highly corrosive liquid | Has a boiling point of 337°C | Is used to make many types of fertilizers | None of these options are correct. | physical_property_reasoning | https://img0.baidu.com/it/u=3181099851,3965974851&fm=253&fmt=auto&app=138&f=JPEG?w=500&h=528 | attribute_reasoning | nan | dev | |
2,001,672 | Which Python code can generate the content of the image? | nan | C | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=20 and height=15')
print(result) | import re
result = re.match(r'(\w+)=(\d+)', 'set width=20 and height=10')
print(result) | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=20 and height=10')
print(result) | import re
result = re.findall(r'(\w+)=(\d+)', 'set width=30 and height=10')
print(result) | structuralized_imagetext_understanding | https://www.runoob.com/python/python-reg-expressions.html | logic_reasoning | nan | dev | |
1,614 | Which category does this image belong to? | nan | C | MRI image | icon | microscopic image | abstract painting | image_style | coarse_perception | nan | dev | ||
1,001,511 | Which corner doesn't have any food? | nan | A | bottom-right | top-right | top-left | bottom-left | object_localization | finegrained_perception (instance-level) | nan | dev | ||
2,001,636 | what python code is gonna generate the result as shown in the image? | nan | D | thisdict = {
"brand": "Ford",
"electric": False,
"year": 1965,
"colors": ["red", "white", "blue"]
}
print(thisdict) | thisdict = dict(name = "John", age = 37, country = "Norway")
print(thisdict) | thisdict = {
"brand": "Ford",
"model": "Mustang",
"year": 1965
}
print(thisdict) | thisdict = {
"brand": "Ford",
"model": "Mustang",
"year": 1965
}
print(thisdict["brand"]) | structuralized_imagetext_understanding | https://www.w3schools.com/python/trypython.asp?filename=demo_dictionary_brand | logic_reasoning | nan | dev | |
1,001,237 | Which image is more brightful? | nan | A | The second image | The first image | nan | nan | image_quality | http://zuohaotu.com/Download/062010433198_039140730.jpg | coarse_perception | nan | dev | |
3,000,047 | Which one is the correct caption of this image? | nan | A | A fire hydrant with a pair of eye stickers making a face on it. | a large food truck is parked on the side of the street | Neither one of these people had a good flight. | People in a horse drawn buggy on a city street. | image_scene | description | coarse_perception | nan | dev | |
1,531 | how many dogs are there？ | nan | B | 3 | 4 | 2 | 6 | object_localization | finegrained_perception (instance-level) | nan | dev | ||
506 | Which can be the associated text with this image posted on twitter | nan | A | Morning: Memeland Evening: Jay Chou 7 sold out nights in #hongkong #JayChou | We will be streaming our Mayday [ Live In the Sky ] online concert tomorrow night: http://bit.ly/YTBinMusic . We go on at 20:00 (GMT+8) May 31st. See you online then. | my little airport 🫶🏼 | Run to Victoria Harbor at night😅 | celebrity_recognition | socialmedia | finegrained_perception (instance-level) | nan | dev | |
1,001,118 | In this comparison picture, are the upper and lower modules the same color? | nan | C | Can't judge | same | Not the same | nan | attribute_comparison | https://www.bing.com/images/search?view=detailV2&ccid=A%2BsFFjRM&id=A792097ACBF1860598926EA11AD8FE64CAB3F61D&thid=OIP.A-sFFjRMu2vXJK4_pHPMTwHaHa&mediaurl=https%3A%2F%2Fimg.zcool.cn%2Fcommunity%2F019dee5e846bf3a80120a89533405e.jpg%401280w_1l_2o_100sh.jpg&exph=1181&expw=1181&q=%e4%b8%a4%e4%b8%aa%e7%89%a9%e4%bd%93%e9%a2%9... | finegrained_perception (cross-instance) | nan | dev | |
3,001,967 | In nature, what's the relationship between these two creatures? | nan | A | Competitive relationships | Parasitic relationships | Symbiotic relationship | Predatory relationships | nature_relation | https://th.bing.com/th/id/OIP.0yxIwfe0i-01dG6jdduCXgHaEK?w=296&h=180&c=7&r=0&o=5&dpr=1.5&pid=1.7 | relation_reasoning | nan | dev | |
3,001,369 | Which mood does this image convey? | nan | B | Anxious | Cozy | Angry | Sad | image_emotion | coarse_perception | nan | dev | ||
2,000,244 | Which of the following could Ernesto's test show? | People can use the engineering-design process to develop solutions to problems. One step in the process is testing if a potential solution meets the requirements of the design.
The passage below describes how the engineering-design process was used to test a solution to a problem. Read the passage. Then answer the ques... | C | which design would have the least traffic noise in the concert area | if at least 20% of the park would be shaded by trees in each design | which design would have the greatest distance between the concert area and the road | nan | identity_reasoning | scienceqa | attribute_reasoning | nan | dev | |
758 | Who is the person in this image? | nan | D | Jing Wu | Xiang Liu | Kobe Bryant | Morgan Freeman | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev | |
2,001,603 | what style is depicted in this image? | nan | C | modernism | dadaism | impressionism | post-Impressionism | image_style | coarse_perception | nan | dev | ||
1,831 | Which of the following captions best describes this image? | nan | C | A person painting a landscape on a canvas. | A group of people watching a play in a theater. | A woman sculpting a statue from clay. | A person taking photographs of a cityscape. | image_scene | coarse_perception | nan | dev | ||
2,000,816 | Which scene category matches this image the best? | nan | D | botanical_garden | jewelry_shop | excavation | forest/broadleaf | image_scene | scene/places365_val | coarse_perception | Places365_val_00000009.jpg | dev | |
3,000,576 | Which action is performed in this image? | nan | B | cooking sausages | making tea | barbequing | making sushi | action_recognition | action/aras | finegrained_perception (cross-instance) | aras_clips/making_tea/eP5_b02cxoo_0.mp4 | dev | |
1,000,646 | Where is the broccoli located in the picture? | nan | D | bottom right | top right | top left | bottom left | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000002765.jpg | dev | |
2,001,374 | Which mood does this image convey? | nan | A | Happy | Angry | Sad | Anxious | image_emotion | coarse_perception | nan | dev | ||
1,815 | Which of the following captions best describes this image? | nan | C | A person swimming in a pool | A group of people sunbathing on a beach | A person skiing down a mountain | A woman doing yoga in a park | image_scene | coarse_perception | nan | dev | ||
1,001,758 | The area of which figure can be calculated using the formula in this picture? | nan | D | Circle. | Square. | Rectangle. | Triangle. | ocr | finegrained_perception (instance-level) | nan | dev | ||
1,713 | What's the function of the demonstrated object? | nan | A | Cooking | Cook soup | Fry | steam | function_reasoning | https://www.bing.com/images/search?view=detailV2&ccid=G7ibfiNv&id=2D6BFB9C13113C3B7EA1791684C398B642B21227&thid=OIP.G7ibfiNvU8ZVHl8JP6asrAHaHa&mediaurl=https%3a%2f%2fwww.wanwupai.com%2fupload%2fproduct%2f20190917-1%2fcbcb8b3a174a26a05db9d0e19212ae3d.png&exph=800&expw=800&q=%e7%82%92%e9%94%85&simid=608051800650558057&FO... | attribute_reasoning | nan | dev | |
346 | What is the name of the place shown? | nan | D | New Hampshire | Connecticut | New York | Rhode Island | object_localization | scienceqa | finegrained_perception (instance-level) | nan | dev | |
3,001,075 | Can you identify the season in which the picture was taken? | nan | C | summer | fall | winter | spring | image_scene | coarse_perception | nan | dev | ||
932 | What's the function of the demonstrated object? | nan | A | It can be easily transported and used in temporary spaces | supply water for suppressing fire | Transportation of people and cargo | Offering a variety of drink | function_reasoning | COCO train2014 | attribute_reasoning | 5.png | dev | |
1,001,483 | what is this? | nan | D | cheese stick | spring roll | mozerella cheese stick | bread stick | celebrity_recognition | finegrained_perception (instance-level) | nan | dev | ||
867 | The picture shows a scene of flame reaction. Please select the metal that most possibly used in this experiment. | nan | C | Copper. | Iron. | Sodium. | Aluminium. | physical_property_reasoning | Internet | attribute_reasoning | https://p1-bk.byteimg.com/tos-cn-i-mlhdmxsy5m/5e0b0364e26c49b19bb722a774d3c934~tplv-mlhdmxsy5m-q75:0:0.image | dev | |
3,001,345 | Which mood does this image convey? | nan | B | Anxious | Happy | Angry | Sad | image_emotion | coarse_perception | nan | dev | ||
3,000,072 | Which one is the correct caption of this image? | nan | C | A man standing near the home plate swinging a bat | An older orange van is parked next to a modern mini van in front of a small shop. | A black kitten laying down next to two remote controls. | A woman is cutting up a block of spam. | image_topic | description | coarse_perception | nan | dev | |
3,000,729 | Who is the person in this image? | nan | A | Leonardo Dicaprio | Steve Jobs | Jackie Chan | Elon Musk | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev | |
2,001,306 | what is the color of this object? | nan | D | yellow | green | red | blue | attribute_recognition | finegrained_perception (instance-level) | nan | dev | ||
54 | Which one is the correct caption of this image? | nan | A | A grey and white bird with red feet and eyes perches on a branch. | A broken flip phone sits, in two pieces, on the counter. | pieces of kiwi and peach cut up on a plate next to a teapot | Three small piece of fried food on a white plate with writing. | image_topic | description | coarse_perception | nan | dev | |
3,000,108 | Which one is the correct caption of this image? | nan | B | A baseball pitcher prepares to deliver a pitch. | A birthday cake with candles and a cell phone. | a couple of big airplanes that are in a tunnel | A man and a young girl playing video games | image_topic | description | coarse_perception | nan | dev | |
3,001,643 | what python code is gonna generate the result as shown in the image? | nan | D | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __str__(self):
return f"{self.name}({self.age})"
p1 = Person("John", 36)
print(p1) | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def myfunc(self):
print("Hello my name is " + self.name)
p1 = Person("John", 36)
p1.myfunc() | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def myfunc(self):
print("Hello my name is " + self.name)
p1 = Person("John", 36)
del p1.age
print(p1.age) | fruits = ["apple", "banana", "cherry"]
for x in fruits:
if x == "banana":
continue
print(x) | structuralized_imagetext_understanding | https://www.w3schools.com/python/trypython.asp?filename=demo_for_continue | logic_reasoning | nan | dev | |
1,321 | what emotion does this emoji express? | nan | A | happy | sad | excited | angry | attribute_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,001,254 | Which image is more brightful? | nan | B | The second image | The first image | nan | nan | image_quality | http://zuohaotu.com/Download/062011032870_0202351926.jpg | coarse_perception | nan | dev | |
3,000,239 | Which of these states is farthest east? | nan | D | Colorado | Michigan | North Dakota | North Carolina | attribute_recognition | scienceqa | finegrained_perception (instance-level) | nan | dev | |
838 | What the nature relations of these animals | nan | B | predation | mutualism | parasitism | nan | nature_relation | internet | relation_reasoning | mutualism_4.jpeg | dev | |
2,000,928 | What's the function of the demonstrated object? | nan | C | Ensuring safety | Maintaining the aircrafts | Transportation of people and cargo. | Providing food and drinks. | function_reasoning | COCO train2014 | attribute_reasoning | 1.png | dev | |
2,001,943 | In nature, what's the relationship between these two creatures? | nan | C | Parasitic relationships | Symbiotic relationship | Predatory relationships | Competitive relationships | nature_relation | https://th.bing.com/th/id/R.c17243402facb00e4abef2c1d4047c3e?rik=XXCoB%2bEPv%2fRsOg&riu=http%3a%2f%2fwww.guangyuanol.cn%2fuploads%2fallimg%2f201105%2f16004KK0-1.png&ehk=pDr5XC6YCc8S2h%2fnPhDli1Kp8sW%2fX9FrcPOxqEKTnMc%3d&risl=&pid=ImgRaw&r=0 | relation_reasoning | nan | dev | |
1,000,523 | What feeling is represented in this image? | nan | C | supportive | engaged | disordered | angry | image_emotion | Internet | coarse_perception | nan | dev | |
1,980 | In nature, what's the relationship between these two creatures? | nan | A | Predatory relationships | Competitive relationships | Parasitic relationships | Symbiotic relationship | nature_relation | https://th.bing.com/th/id/R.7cdab3780771098fbedcdc6798883e07?rik=UyOVb%2bw7U8f5BA&riu=http%3a%2f%2fimg.coozhi.com%2fupload%2f20200615%2f15t9r220u9m23p27cdab3780771098fbedcdc6798883e07.0x750x450.jpg&ehk=%2bTBTz%2fHtKH8eB6e6lfGmyuQej8W1HQnq9H8V3nDEiug%3d&risl=&pid=ImgRaw&r=0 | relation_reasoning | nan | dev | |
3,000,734 | Who is the person in this image? | nan | A | Jing Wu | Morgan Freeman | Jay Chou | Kobe Bryant | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev | |
1,718 | What's the function of the demonstrated object? | nan | B | grill | filtration | flavouring | Pick-up | function_reasoning | https://www.bing.com/images/search?view=detailV2&ccid=uLaUo1eq&id=3D01E1E012E7DC23B885AB3EA25CB9951D9723AC&thid=OIP.uLaUo1eqzwRACOIxKrn3pwHaHa&mediaurl=https%3a%2f%2fimg.directindustry-china.cn%2fimages_di%2fphoto-g%2f63760-15045837.jpg&exph=1500&expw=1500&q=%e6%bc%8f%e6%96%97&simid=608045620199968982&FORM=IRPRST&ck=51... | attribute_reasoning | nan | dev | |
1,001,538 | The object shown in this figure: | nan | B | Is the most abundant element in the universe. | Is a colorless, odorless gas. | Can be ionized to produce a plasma. | Has a high boiling point compared to other noble gases. | physical_property_reasoning | https://image.baidu.com/search/detail?ct=503316480&z=&tn=baiduimagedetail&ipn=d&word=%E6%B0%A6&step_word=&ie=utf-8&in=&cl=2&lm=-1&st=-1&hd=&latest=©right=&cs=4215392,2179438032&os=2766074397,4250466693&simid=4215392,2179438032&pn=1&rn=1&di=7214885350303334401&ln=1473&fr=&fmq=1687242100404_R&ic=0&s=undefined&se=&sme... | attribute_reasoning | nan | dev | |
1,001,751 | Which special day is associated with this poster? | nan | D | Mother's Day | Earth Day. | National Reading Day. | World Water Day. | ocr | https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcQvoMjXHzu84g50xKIJTJhUhQJ6wCwU_f5m1A&usqp=CAU | finegrained_perception (instance-level) | nan | dev | |
3,000,345 | What is the name of the place shown? | nan | D | Michigan | Kentucky | Maryland | Virginia | object_localization | scienceqa | finegrained_perception (instance-level) | nan | dev | |
2,001,526 | where is the cat? | nan | B | bottom-left | bottom-right | top-right | top-left | object_localization | finegrained_perception (instance-level) | nan | dev | ||
1,001,816 | Which of the following captions best describes this image? | nan | A | A woman doing yoga in a park | A person swimming in a pool | A group of people sunbathing on a beach | A person skiing down a mountain | image_scene | coarse_perception | nan | dev | ||
1,426 | who is this person? | nan | B | David Beckham | Prince Harry | Daniel Craig | Tom Hardy | celebrity_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,000,070 | Which one is the correct caption of this image? | nan | D | a laptop a mouse a desk and some wires | some clouds a traffic light and some buildings | A man walks through the ocean water with a surfboard under his arm. | A vehicle is shown transporting a shipment of bicycles. | image_scene | description | coarse_perception | nan | dev | |
3,001,447 | who is this person? | nan | B | Salman Khan | Shah Rukh Khan | Bruce Lee | Jackie Chan | celebrity_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,248 | Which image is more brightful? | nan | A | The first image | The second image | nan | nan | image_quality | http://zuohaotu.com/Download/062010541415_0137841242.jpg | coarse_perception | nan | dev | |
767 | Who is the person in this image? | nan | D | Bill Gates | Steve Jobs | Donald Trump | Lionel Messi | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev | |
670 | How many people are visible in this picture? | nan | D | three | six | seven | eight | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000001412.jpg | dev | |
1,691 | What's the function of the demonstrated object? | nan | C | Draw | cut | deposit | refrigeration | function_reasoning | https://www.bing.com/images/search?view=detailV2&ccid=UWT2Frvh&id=E3C6D7348E248416861754E687064D1A44F2F78F&thid=OIP.UWT2FrvhTgr4O7F1ohPZswHaHa&mediaurl=https%3a%2f%2fimg.zcool.cn%2fcommunity%2f01747e59e6df82a801202b0ca96099.png%401280w_1l_2o_100sh.png&exph=1280&expw=1280&q=%e4%bf%9d%e9%99%a9%e6%9f%9c&simid=608052079808... | attribute_reasoning | nan | dev | |
3,001,500 | How many bananas are there in the image? | nan | A | 2 | 4 | 5 | 3 | object_localization | finegrained_perception (instance-level) | nan | dev | ||
646 | Where is the broccoli located in the picture? | nan | C | top right | top left | bottom left | bottom right | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000002765.jpg | dev | |
2,001,765 | The volume of which object can be calculated using the formula in the figure? | nan | A | Cone. | Sphere. | Cuboid. | Cylinder. | ocr | finegrained_perception (instance-level) | nan | dev | ||
3,000,534 | Which emotion is being depicted in this image? | nan | A | sadness | anger | loneliness | happiness | image_emotion | Internet | coarse_perception | nan | dev | |
1,001,273 | which image is more colorful? | nan | A | The second image | The first image | nan | nan | image_quality | http://zuohaotu.com/Download/062011324186_01473138944.jpg | coarse_perception | nan | dev | |
3,001,706 | What's the function of the demonstrated object? | nan | A | Measure the temperature | burnish | Brushing | Cut the grass | function_reasoning | https://www.bing.com/images/search?view=detailV2&ccid=gS%2F601OH&id=6313295FA6CC76490D7C415FD47DE725FF0B18B6&thid=OIP.gS_601OH_FROnbg0aT89YwHaHa&mediaurl=https%3A%2F%2Fcbu01.alicdn.com%2Fimg%2Fibank%2F2018%2F496%2F942%2F9073249694_101079264.jpg&exph=1920&expw=1920&q=%e6%b8%a9%e5%ba%a6%e8%ae%a1&simid=608002253913859744&... | attribute_reasoning | nan | dev | |
1,001,120 | In this comparison picture, are the left and right modules the same shape? | nan | C | Can't judge | same | Not the same | nan | attribute_comparison | https://www.bing.com/images/search?view=detailV2&ccid=77rYhcri&id=8A298E84DE3EB3731E6B59EF6D14777464FB901C&thid=OIP.77rYhcribbmGpzi3gbNhrgHaDq&mediaurl=https%3A%2F%2Fimg.zcool.cn%2Fcommunity%2F0157c45da03b3da80121b722b1d2b3.jpg%401280w_1l_2o_100sh.jpg&exph=632&expw=1280&q=%e4%b8%a4%e4%b8%aa%e7%89%a9%e4%bd%93%e9%a2%9c%e... | finegrained_perception (cross-instance) | nan | dev | |
1,757 | The area of which figure can be calculated using the formula in this picture? | nan | D | Square. | Rectangle. | Triangle. | Circle. | ocr | finegrained_perception (instance-level) | nan | dev | ||
2,001,026 | What is the intended outcome in this image? | nan | A | She will grow her leg muscle | She will undergo surgery to reduce leg muscle | She will lose leg muscle | She will maintain her current leg muscle size | future_prediction | Internet | logic_reasoning | nan | dev | |
1,000,655 | In the picture, which direction is the cat facing? | nan | D | upward | right | left | facing the camera | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000006321.jpg | dev | |
3,000,182 | In the image, what does the skateboarder's jump off the city bench demonstrate? | nan | B | The skateboarder's fearlessness and recklessness. | The skateboarder's impressive skill, balance, and control. | The skateboarder's interest in urban landscapes. | The skateboarder's lack of expertise and control. | function_reasoning | reasoning | attribute_reasoning | nan | dev | |
2,000,319 | Which solution has a higher concentration of blue particles? | The diagram below is a model of two solutions. Each blue ball represents one particle of solute. | A | Solution B | neither; their concentrations are the same | Solution A | nan | attribute_comparison | scienceqa | finegrained_perception (cross-instance) | nan | dev | |
2,001,332 | Which mood does this image convey? | nan | C | Happy | Angry | Sad | Anxious | image_emotion | https://th.bing.com/th/id/OIP.-_959ECGfWjdPEJpE1gjowAAAA?w=268&h=180&c=7&r=0&o=5&dpr=1.5&pid=1.7 | coarse_perception | nan | dev | |
2,000,654 | In the picture, which direction is the man facing? | nan | D | left | right | back to the camera | facing the camera | object_localization | COCO_test2015 | finegrained_perception (instance-level) | 000000005978.jpg | dev | |
3,000,118 | Which one is the correct caption of this image? | nan | B | A corner bathtub in a very clean bathroom. | Three men all eating sub sandwiches at a restaurant. | a cat that is drinking out of a sink | You will not get anywhere if you open these doors and try to pass through. | action_recognition | description | finegrained_perception (cross-instance) | nan | dev | |
1,001,267 | which image is more colorful? | nan | A | The second image | The first image | nan | nan | image_quality | http://zuohaotu.com/Download/062011223063_0516771790.jpg | coarse_perception | nan | dev | |
2,001,843 | What direction is France in the Mediterranean Sea? | nan | B | west | north | east | south | spatial_relationship | https://www.google.com/maps/@44.3563054,26.1089918,4z?entry=ttu | finegrained_perception (cross-instance) | nan | dev | |
3,000,199 | Based on the image, what is one advantage of indoor skateboarding practice compared to outdoor skateboarding? | nan | D | Indoor skateboarding allows for more opportunities to interact with pedestrians and traffic. | Indoor skateboarding facilities offer better lighting conditions for visibility. | Indoor skateboarding hinders the progress of skateboarders due to limited space. | Indoor skateboarding provides a controlled environment for focusing on specific tricks and stunts. | function_reasoning | reasoning | attribute_reasoning | nan | dev | |
2,001,397 | What's the profession of the people in this picture? | nan | A | electrician | tailor | driver | teacher | identity_reasoning | attribute_reasoning | nan | dev | ||
1,000,264 | Which better describes the tide pool ecosystems in Tongue Point Marine Life Sanctuary? | Figure: Tongue Point Marine Life Sanctuary.
Tongue Point Marine Life Sanctuary is in western Washington State. The park is on the coast of the Pacific Ocean. It has many tide pool ecosystems. | A | It has water that is rich in nutrients. It also has many different types of organisms. | It has water that is poor in nutrients. It also has only a few types of organisms. | nan | nan | physical_property_reasoning | scienceqa | attribute_reasoning | nan | dev | |
2,001,645 | what python code is gonna generate the result as shown in the image? | nan | A | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def myfunc(self):
print("Hello my name is " + self.name)
p1 = Person("John", 36)
p3.myfunc() | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def myfunc(self):
print("Hello my name is " + self.name)
p1 = Person("John", 36)
del p1.age
print(p3.age) | fruits = ["apple", "banana", "cherry"]
for x in fruits:
if x == "banana":
continue
print(x) | class Person:
def __init__(self, name, age):
self.name = name
self.age = age
def __str__(self):
return f"{self.name}({self.age})"
p1 = Person("John", 36)
print(p3) | structuralized_imagetext_understanding | https://www.w3schools.com/python/trypython.asp?filename=demo_class4 | logic_reasoning | nan | dev | |
2,001,106 | Are the two horses in the picture the same size? | nan | A | Not the same | Can't judge | same | nan | attribute_comparison | https://www.bing.com/images/search?view=detailV2&ccid=Z09Xhc8c&id=460890B11CA27841E911383B544B574F6E677021&thid=OIP.Z09Xhc8c8YpoNU9S8rZdOQHaEo&mediaurl=https%3A%2F%2Ffsimg1.xbdedu.cn%2F2015%2F08%2F0871121A-6015-969B-0A8D-A2143AEC4D86.png&exph=413&expw=660&q=%e4%b8%a4%e4%b8%aa%e7%89%a9%e4%bd%93%e5%af%b9%e6%af%94%e5%9b%b... | finegrained_perception (cross-instance) | nan | dev | |
1,001,323 | what emotion does this emoji express? | nan | B | angry | happy | sad | excited | attribute_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,000,734 | Who is the person in this image? | nan | C | Jay Chou | Kobe Bryant | Jing Wu | Morgan Freeman | celebrity_recognition | Google | finegrained_perception (instance-level) | nan | dev | |
2,001,464 | what landmark is this? and where is it? | nan | B | The Taj Mahal in Agra, India | Machu Picchu in Peru | Windmills at Kinderdijk, Holland | The Great Chinese Wall in China | celebrity_recognition | finegrained_perception (instance-level) | nan | dev | ||
1,001,361 | Which mood does this image convey? | nan | B | Angry | Sad | Anxious | Happy | image_emotion | coarse_perception | nan | dev |
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