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* colors expression by KMean algorithm * object detection by imageai * object detection by cvlib * add encapsulation of object detection * remove encapsulation of objdetect v0 * objects expression to dict * [pre-commit.ci] auto fixes from pre-commit.com hooks for more information, see https://pre-commit.ci * added imageai to requirements * add objects to dictionary * update for AnalysisMethod baseline * add objects dection support explore_analysis display * extend python version of misinf to allow imageai * account for older python * use global functionality for dict to csv convert * update for docker build * docker will build now but ipywidgets still not working * test code * include test data folder in repo * add some sample images * load cvs labels to dict * add test data * retrigger checks * add map to human coding * get orders from dict, missing dep * add module to test accuracy * retrigger checks * retrigger checks * now removing imageai * removed imageai * move labelmanager to analyse * multiple faces in mydict * fix pre-commit issues * map mydict * hide imageai * objects default using cvlib, isolate and disable imageai * correct python version * refactor faces tests * refactor objects tests * sonarcloud issues * refactor utils tests * address code smells * update readme * update notebook without imageai Co-authored-by: Ma Xianghe <825074348@qq.com> Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com> Co-authored-by: iulusoy <inga.ulusoy@uni-heidelberg.de>
127 строки
5.0 KiB
JSON
127 строки
5.0 KiB
JSON
{
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"V9_4": {
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"order": 169,
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"variable_label": "4=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Person visible",
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"variable_coding": "Bool",
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"variable_comment": "Yes if there's someone shown",
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"variable_mydict": "face",
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"value_mydict": "Yes"
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},
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"V9_5a": {
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"order": 170,
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"variable_label": "5a=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "More than one person shown",
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"variable_coding": "Bool",
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"variable_comment": "Yes if there are several individuals who appear in the post (do not count profile pictures)",
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"variable_mydict": "multiple_faces",
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"value_mydict": "Yes"
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},
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"V9_5b": {
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"order": 171,
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"variable_label": "5b=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "How many people shown?",
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"variable_coding": "Int",
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"variable_comment": "If more than 15, put 99",
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"variable_mydict": "no_faces",
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"value_mydict": "0"
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},
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"V9_6": {
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"order": 172,
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"variable_label": "6=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Face fully visible",
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"variable_coding": "Bool",
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"variable_comment": "Yes if you can see all their face (no mask on)",
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"variable_mydict": "wears_mask",
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"value_mydict": "No"
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},
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"V9_7": {
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"order": 173,
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"variable_label": "7=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Face ONLY partially visible",
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"variable_coding": "Bool",
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"variable_comment": "Yes if you can only see part of their face, including when they are wearing a mask",
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"variable_mydict": "wears_mask",
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"value_mydict": "Yes"
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},
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"V9_8": {
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"order": 174,
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"variable_label": "8=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Facial positive expression",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they display some kind of positive facial expression (smiling, happy, relieved, hopeful etc.)",
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"variable_mydict": "emotion (category)",
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"value_mydict": "Positive"
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},
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"V9_8a": {
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"order": 175,
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"variable_label": "8a=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Positive expression: happiness",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they display happiness",
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"variable_mydict": "emotion",
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"value_mydict": "happy"
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},
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"V9_9": {
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"order": 176,
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"variable_label": "9=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Facial negative expression",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they display some kind of negative facial expression (crying, showing ager, fear, disgust etc.)",
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"variable_mydict": "emotion (category)",
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"value_mydict": "Negative"
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},
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"V9_10": {
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"order": 177,
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"variable_label": "10=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Negative expression: anxiety",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they show fear or anxiety. If you can't tell, choose No=0",
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"variable_mydict": "emotion",
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"value_mydict": "fear"
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},
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"V9_11": {
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"order": 178,
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"variable_label": "11=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Negative expression: anger",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they show anger or outrage. If you can't tell, choose No=0",
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"variable_mydict": "emotion",
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"value_mydict": "angry"
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},
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"V9_12": {
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"order": 179,
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"variable_label": "12=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Negative expression: disgust",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they show disgust. If you can't tell, choose No=0",
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"variable_mydict": "emotion",
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"value_mydict": "disgust"
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},
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"V9_13": {
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"order": 180,
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"variable_label": "13=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Negative expression: other, specify",
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"variable_coding": "Bool",
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"variable_comment": "Yes if they show any other negative emotion, please specify. If you can't tell, choose No=0",
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"variable_mydict": "emotion",
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"value_mydict": "sad"
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},
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"V9_13_text": {
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"order": 181,
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"variable_label": "13=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Negative expression: other, specify",
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"variable_coding": "Str",
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"variable_mydict": "emotion",
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"value_mydict": ""
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},
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"V11_3": {
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"order": 189,
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"variable_label": "111_3=PICTURE_SPECIFIC_VisualONLY",
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"variable_explanation": "Respect of the rules",
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"variable_coding": "Bool",
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"variable_comment": "Yes if the post shows mask wearing, vaccine taking, social distancing, any proof of respecting the rules",
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"variable_mydict": "wears_mask",
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"value_mydict": "Yes"
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}
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} |