Updates to CellDB

CellCounting/models/train_model.py

-#!/usr/bin/enc python
+#!/usr/bin/env python
 
 # Train model for cell recognition
 # Oiwi, 07/2018
@@ -8,8 +8,8 @@
 
 #  General
 import numpy as np
-import time
-import os
+import time, os, sys
+import argparse
 # DL stuff
 from keras.models import Sequential
 from keras.layers.convolutional import Convolution2D, MaxPooling2D
@@ -21,7 +21,7 @@ from keras.preprocessing.image import ImageDataGenerator
 # Other
 import pandas as pd
 from CellCounting.utils import db
-import argparse
+
 
 # ------------------------------ DATA ------------------------------ #
 def prepare_data(celldb, args):
@@ -200,6 +200,7 @@ def main():
     print('Preparing image database')
     celldb = db.CellDB()
     celldb.load(args.data)
+    print(celldb)
     celldb.equalise_classes()
     
     print('Preparing and training model')

CellCounting/utils/db.py

@@ -123,3 +123,23 @@ class CellDB(object):
             print('                                               ')
         print('-----------------------------------------------')
         return
+
+    # Check prediction against true classes
+    def check_prediction_yn(self, labels, verbose=False):
+        TP = ((self.cell_counts>0) & (labels>0)).sum()
+        FP = ((self.cell_counts==0) & (labels>0)).sum()
+        TN = ((self.cell_counts==0) & (labels==0)).sum()
+        FN = ((self.cell_counts>0) & (labels==0)).sum()
+
+        recall = TP/(TP+FN)
+        prec   = TN/(TN+FP)
+        acc    = (TP+TN)/(TP+FP+TN+FN)
+
+        if verbose:
+            print('Accuracy  = {:.2f}'.format(acc*100))
+            print('Precision = {:.2f}'.format(prec*100))
+            print('Recall    = {:.2f}'.format(recall*100))
+                  
+        
+        
+        return prec, recall, acc