From 1839e98107ae3caba3d9b6d52f27e7ed8876a587 Mon Sep 17 00:00:00 2001 From: Inga Ulusoy Date: Tue, 2 May 2023 12:59:51 +0200 Subject: [PATCH] more cleanup --- ammico/cropposts.py | 17 ++--- ammico/data/map_test_set.json | 127 ---------------------------------- ammico/objects_cvlib.py | 2 - ammico/test/test_faces.py | 1 - ammico/text.py | 1 - 5 files changed, 5 insertions(+), 143 deletions(-) delete mode 100644 ammico/data/map_test_set.json diff --git a/ammico/cropposts.py b/ammico/cropposts.py index c36ff69..7f3e90c 100644 --- a/ammico/cropposts.py +++ b/ammico/cropposts.py @@ -146,7 +146,9 @@ def crop_posts_image( ): """ get file lists from dir and sub dirs - ref_view：ref_view for crop the posts images + + + ref_view： ref_view for crop the posts images view: posts image that need cropping rte： None - not cropped, or (crop_view, number of matches) """ @@ -185,7 +187,7 @@ def crop_posts_image( def get_file_list(dir, filelist, ext=None, convert_unix=True): """ get file lists from dir and sub dirs - dir：root dir for file lists + dir： root dir for file lists ext: file extension rte： File list """ @@ -252,11 +254,9 @@ def crop_posts_from_files( def test_crop_from_file(): # Load images - # view1 = np.array(Image.open("data/ref/ref-00.png")) / 255 - # view2 = np.array(Image.open("data/napsa/100539_ben.png")) / 255 view1 = np.array(Image.open("data/ref/ref-06.png")) view2 = np.array(Image.open("data/napsa/102956_eng.png")) - crop_view, match_num = crop_posts_image(view1, view2, plt_match=True, plt_crop=True) + crop_view, _ = crop_posts_image(view1, view2, plt_match=True, plt_crop=True) cv2.imwrite("data/crop_100489_ind.png", crop_view) @@ -267,10 +267,3 @@ def test_crop_from_folder(): crop_posts_from_files( ref_dir, crop_dir, save_crop_dir, plt_match=False, plt_crop=False ) - - -# do tests: - -# test_crop_from_file() - -# test_crop_from_folder() diff --git a/ammico/data/map_test_set.json b/ammico/data/map_test_set.json deleted file mode 100644 index ecbe0c1..0000000 --- a/ammico/data/map_test_set.json +++ /dev/null @@ -1,127 +0,0 @@ -{ - "v9_4": { - "order": 169, - "variable_label": "4=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Person visible", - "variable_coding": "Bool", - "variable_comment": "Yes if there's someone shown", - "variable_mydict": "face", - "value_mydict": "Yes" - }, - "v9_5a": { - "order": 170, - "variable_label": "5a=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "More than one person shown", - "variable_coding": "Bool", - "variable_comment": "Yes if there are several individuals who appear in the post (do not count profile pictures)", - "variable_mydict": "multiple_faces", - "value_mydict": "Yes" - }, - "v9_5b": { - "order": 171, - "variable_label": "5b=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "How many people shown?", - "variable_coding": "Int", - "variable_comment": "If more than 15, put 99", - "variable_mydict": "no_faces", - "value_mydict": "0" - }, - "v9_6": { - "order": 172, - "variable_label": "6=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Face fully visible", - "variable_coding": "Bool", - "variable_comment": "Yes if you can see all their face (no mask on)", - "variable_mydict": "wears_mask", - "value_mydict": "No" - }, - "v9_7": { - "order": 173, - "variable_label": "7=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Face ONLY partially visible", - "variable_coding": "Bool", - "variable_comment": "Yes if you can only see part of their face, including when they are wearing a mask", - "variable_mydict": "wears_mask", - "value_mydict": "Yes" - }, - "v9_8": { - "order": 174, - "variable_label": "8=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Facial positive expression", - "variable_coding": "Bool", - "variable_comment": "Yes if they display some kind of positive facial expression (smiling, happy, relieved, hopeful etc.)", - "variable_mydict": "emotion (category)", - "value_mydict": "Positive" - }, - "v9_8a": { - "order": 175, - "variable_label": "8a=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Positive expression: happiness", - "variable_coding": "Bool", - "variable_comment": "Yes if they display happiness", - "variable_mydict": "emotion", - "value_mydict": "happy" - }, - "v9_9": { - "order": 176, - "variable_label": "9=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Facial negative expression", - "variable_coding": "Bool", - "variable_comment": "Yes if they display some kind of negative facial expression (crying, showing ager, fear, disgust etc.)", - "variable_mydict": "emotion (category)", - "value_mydict": "Negative" - }, - "v9_10": { - "order": 177, - "variable_label": "10=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Negative expression: anxiety", - "variable_coding": "Bool", - "variable_comment": "Yes if they show fear or anxiety. If you can't tell, choose No=0", - "variable_mydict": "emotion", - "value_mydict": "fear" - }, - "v9_11": { - "order": 178, - "variable_label": "11=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Negative expression: anger", - "variable_coding": "Bool", - "variable_comment": "Yes if they show anger or outrage. If you can't tell, choose No=0", - "variable_mydict": "emotion", - "value_mydict": "angry" - }, - "v9_12": { - "order": 179, - "variable_label": "12=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Negative expression: disgust", - "variable_coding": "Bool", - "variable_comment": "Yes if they show disgust. If you can't tell, choose No=0", - "variable_mydict": "emotion", - "value_mydict": "disgust" - }, - "v9_13": { - "order": 180, - "variable_label": "13=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Negative expression: other, specify", - "variable_coding": "Bool", - "variable_comment": "Yes if they show any other negative emotion, please specify. If you can't tell, choose No=0", - "variable_mydict": "emotion", - "value_mydict": "sad" - }, - "v9_13_text": { - "order": 181, - "variable_label": "13=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Negative expression: other, specify", - "variable_coding": "Str", - "variable_mydict": "emotion", - "value_mydict": "" - }, - "v11_3": { - "order": 189, - "variable_label": "111_3=PICTURE_SPECIFIC_VisualONLY", - "variable_explanation": "Respect of the rules", - "variable_coding": "Bool", - "variable_comment": "Yes if the post shows mask wearing, vaccine taking, social distancing, any proof of respecting the rules", - "variable_mydict": "wears_mask", - "value_mydict": "Yes" - } -} \ No newline at end of file diff --git a/ammico/objects_cvlib.py b/ammico/objects_cvlib.py index 817f522..2ad1e6a 100644 --- a/ammico/objects_cvlib.py +++ b/ammico/objects_cvlib.py @@ -1,7 +1,5 @@ import cv2 import cvlib as cv -import numpy as np -from PIL import Image def objects_from_cvlib(objects_list: list) -> dict: diff --git a/ammico/test/test_faces.py b/ammico/test/test_faces.py index 06d49b1..bb5926d 100644 --- a/ammico/test/test_faces.py +++ b/ammico/test/test_faces.py @@ -1,6 +1,5 @@ import ammico.faces as fc import json -import pytest def test_analyse_faces(get_path): diff --git a/ammico/text.py b/ammico/text.py index c70d528..cd029a5 100644 --- a/ammico/text.py +++ b/ammico/text.py @@ -113,7 +113,6 @@ class TextDetector(utils.AnalysisMethod): self.subdict["text_english_correct"] = str(self.textblob.correct()) def sentiment_analysis(self): - # self.subdict["sentiment"] = self.doc._.blob.sentiment_assessments.assessments # polarity is between [-1.0, 1.0] self.subdict["polarity"] = self.doc._.blob.polarity # subjectivity is a float within the range [0.0, 1.0]