Test suite setup

src/helpers/test/knn.py

@@ -4,6 +4,7 @@ import csv
 from sklearn.preprocessing import MinMaxScaler, StandardScaler, RobustScaler, MaxAbsScaler
 import argparse
 from enum import Enum
+import yaml
 
 parser = argparse.ArgumentParser(prog='KNN Train CLI')
 parser.add_argument('-i', '--input', help='Input CSV file', required=True)
@@ -21,6 +22,8 @@ class Tree(Enum):
 
 class CVSuiteTestKNN: 
     def __init__(self, model = None):
+        self.scale = []
+        
         if model is None:
             self.knn = cv.ml.KNearest_create()
             self.trained = False
@@ -69,6 +72,8 @@ class CVSuiteTestKNN:
             # scaler = MinMaxScaler()
             scaler = MaxAbsScaler()
 
+            # Perform standard scaling
+            self.scale.append(scaler.fit(column))
             column = scaler.fit_transform(column)
             
             # Reshape it back cus scaler is dumb af

src/suite.py

@@ -1,13 +1,20 @@
 #!/usr/bin/python3
+
+# Path tools
 import pathlib
 import glob
-import json
 import datetime
-import os
 import copy
+
+# File IO
 from io import open
+import os
+import json
+
+# OpenCV
 import numpy as np
 import cv2
+from sklearn.preprocessing import MinMaxScaler, StandardScaler, RobustScaler, MaxAbsScaler
 
 # GUI
 import pygubu
@@ -15,7 +22,7 @@ import matplotlib.pyplot as plt
 
 # Helpers
 from helpers.statistics import imgStats
-from helpers.logger import CVSuiteLogger, C_DBUG
+from helpers.logger import CVSuiteLogger, C_DBUG, C_WARN
 from helpers.canvas import CVSuiteCanvas
 from helpers.sift import getSiftData
 
@@ -35,6 +42,7 @@ config_json = json.load(config_file)
 ## UI class setup
 class CVSuite:
     def __init__(self, master=None):
+        # Pygubu builder
         self.builder = builder = pygubu.Builder()
         builder.add_resource_path(PROJECT_PATH)
         builder.add_from_file(PROJECT_UI)
@@ -85,7 +93,10 @@ class CVSuite:
         builder.connect_callbacks(self)
 
         # Model tests
-        self.test_knn = CVSuiteTestKNN(config_json["models"]["knn"])
+        if config_json["models"]["knn"] != "":
+            self.test_knn = CVSuiteTestKNN(config_json["models"]["knn"])
+        else:
+            self.test_knn = None
 
         # Load values from config after UI has been initialised
         self.img_path.set(config_json["path"])
@@ -273,13 +284,26 @@ class CVSuite:
             self.log.add(f"Mean {label}", mean[idx])
             self.log.add(f"Std {label}", std[idx])
 
-    def runTest(self, event=None):
+    def runTest(self, data, event=None):
         output = self.builder.get_object("testdata")
         output.configure(state="normal")
         output.delete(1.0, "end")
         
-        output.insert("end", "test\n")
+        # Normalise data
+        tag = data.pop(0)
+        photoId = data.pop(1)
         
+        print(data)
+        for value in data:
+            print(value)
+        
+        if self.test_knn is not None:
+            # Do knn test
+            output.insert("end", "KNN Result:\n")
+            pass
+        else:
+            print(C_WARN, "KNN Model not configured!")
+
         output.configure(state="disabled")
 
     def updatePath(self):
@@ -422,7 +446,7 @@ class CVSuite:
             self.log.add("SIFT average response", siftData[6])
 
             # Run tests
-            self.runTest()
+            self.runTest(self.log.data)
 
             # Write results to CSV file
             if not part_update: