Parcourir la source

add of extractions stats python scripts

Jérôme BUISINE il y a 3 ans
Parent
commit
11a51d7930
2 fichiers modifiés avec 121 ajouts et 0 suppressions
  1. 57 0
      utils/extract_stats_freq_and_min.py
  2. 64 0
      utils/extract_stats_freq_and_min_all.py

+ 57 - 0
utils/extract_stats_freq_and_min.py

@@ -0,0 +1,57 @@
+# main imports
+import os, sys
+import argparse
+import json
+import numpy as np
+
+
+def main():
+    """
+    main function which is ran when launching script
+    """ 
+    parser = argparse.ArgumentParser(description="Extract scenes data and save thresholds into .csv")
+
+    parser.add_argument('--file', type=str, help='image to convert', required=True)
+    parser.add_argument('--output', type=str, help='output csv filename', required=True)
+
+    args = parser.parse_args()
+
+    p_file   = args.file
+    p_output = args.output
+
+    f = open(p_file)
+    json_data = json.load(f)
+
+    dict_data = {}
+
+    for element in json_data:
+
+        scene = element['msg']['sceneName']
+
+        if scene not in dict_data:
+            dict_data[scene] = {}
+
+        extracts = element['msg']['extracts']
+
+        for extract in extracts:
+            if extract['index'] not in dict_data[scene]:
+                dict_data[scene][extract['index']] = [extract['quality']]
+            else:
+                dict_data[scene][extract['index']].append(extract['quality'])
+            
+    
+    output_file = open(p_output, 'w')
+
+    for scene in dict_data:
+        output_file.write(scene + ';')
+        
+        for extract in dict_data[scene]:
+            thresholds_data = dict_data[scene][extract]
+            output_file.write(str(int(np.min(thresholds_data))) + ';')
+
+        output_file.write('\n')
+
+
+
+if __name__ == "__main__":
+    main()

+ 64 - 0
utils/extract_stats_freq_and_min_all.py

@@ -0,0 +1,64 @@
+# main imports
+import os, sys
+import argparse
+import json
+import numpy as np
+
+
+def main():
+    """
+    main function which is ran when launching script
+    """ 
+    parser = argparse.ArgumentParser(description="Extract scenes data and save thresholds into .csv")
+
+    parser.add_argument('--file', type=str, help='image to convert', required=True)
+    parser.add_argument('--output', type=str, help='output csv filename', required=True)
+
+    args = parser.parse_args()
+
+    p_file   = args.file
+    p_output = args.output
+
+    f = open(p_file)
+    json_data = json.load(f)
+
+    dict_data = {}
+
+    for element in json_data:
+
+        scene = element['msg']['sceneName']
+
+        if scene not in dict_data:
+            dict_data[scene] = {}
+
+        extracts = element['msg']['extracts']
+
+        for extract in extracts:
+            if extract['index'] not in dict_data[scene]:
+                dict_data[scene][extract['index']] = [extract['quality']]
+            else:
+                dict_data[scene][extract['index']].append(extract['quality'])
+            
+    
+    output_file = open(p_output, 'w')
+    output_file.write('scene;n_users;min_scene;\n')
+
+    for scene in dict_data:
+        output_file.write(scene + ';')
+        
+        all_thresholds = []
+        n_users = 0
+        for extract in dict_data[scene]:
+            thresholds_data = dict_data[scene][extract]
+            
+            all_thresholds.append(int(np.min(thresholds_data)))
+            n_users = len(thresholds_data)
+
+        output_file.write(str(n_users) + ';' + str(np.min(all_thresholds)) + ';')
+
+        output_file.write('\n')
+
+
+
+if __name__ == "__main__":
+    main()