reorganizing files

add train
some catches

dto/annotationClass.py

@@ -0,0 +1,23 @@
+import json
+from os.path import dirname, join
+
+
+class AnnotationClass:
+    def __init__(self, id, name, color):
+        self.id = id
+        self.name = name
+        self.color = color
+
+    @staticmethod
+    def read_json():
+        classes_path = join(dirname(dirname(__file__)), 'classes.json')
+        with open(classes_path, 'r', encoding='utf-8') as f:
+            j = json.loads(f.read())
+            return {cl['Id']: AnnotationClass(id=cl['Id'], name=cl['Name'], color=cl['Color']) for cl in j}
+
+    @property
+    def color_tuple(self):
+        color = self.color[3:]
+        lv = len(color)
+        xx = range(0, lv, lv // 3)
+        return tuple(int(color[i:i + lv // 3], 16) for i in xx)

dto/imageLabel.py

@@ -0,0 +1,32 @@
+import cv2
+from matplotlib import pyplot as plt
+
+
+class ImageLabel:
+    def __init__(self, image_path, image, labels_path, labels):
+        self.image_path = image_path
+        self.image = image
+        self.labels_path = labels_path
+        self.labels = labels
+
+    def visualize(self, annotation_classes):
+        img = cv2.cvtColor(self.image.copy(), cv2.COLOR_BGR2RGB)
+        height, width, channels = img.shape
+        for label in self.labels:
+            class_num = int(label[-1])
+            x_c = float(label[0])
+            y_c = float(label[1])
+            w = float(label[2])
+            h = float(label[3])
+            x_min = x_c - w / 2
+            y_min = y_c - h / 2
+            x_max = x_min + w
+            y_max = y_min + h
+            color = annotation_classes[class_num].color_tuple
+
+            cv2.rectangle(img, (int(x_min * width), int(y_min * height)), (int(x_max * width), int(y_max * height)),
+                          color=color, thickness=3)
+        plt.figure(figsize=(12, 12))
+        plt.axis('off')
+        plt.imshow(img)
+        plt.show()