image-recognizer/ui/front_page/sections/neural_net_info_widget.py

import tkinter as tk

from ui.app_state import AppState
from ui.components.label_with_refresh import LabelWithRefresh


class NeuralNetInfoWidget(tk.Frame):
    def __init__(self, parent, app_state: AppState):
        super().__init__(parent)
        self.app_state = app_state
        self.update_ui()

    def clear_ui(self):
        for widget in self.winfo_children():
            widget.destroy()

    def update_ui(self):
        self.clear_ui()
        row = 0
        if self.app_state.neural_net is not None:
            for layer in self.app_state.neural_net.layers:
                (tk.Label(self, text=f"{layer.type} {layer.index}")
                    .grid(column=0, row=row, padx=10, pady=5, sticky='w'))
                tk.Label(self, text=f"{layer.input_dim} -> {layer.output_dim} neurons").grid(column=1, row=row, padx=10, pady=5, sticky='e')
                row += 1

            button_state = tk.DISABLED
            if self.app_state.model_data is not None:
                button_state = tk.NORMAL

            tk.Label(self, text="Accuracy:").grid(column=0, row=row, padx=10, pady=5, sticky='w')
            last_accuracy = "NA"
            if self.app_state.neural_net.last_accuracy is not None:
                last_accuracy = f"{self.app_state.neural_net.last_accuracy * 100:.2f}%"
            self.accuracy_label = LabelWithRefresh(self, last_accuracy, callback=self.recalculate_accuracy, initial_state=button_state)
            self.accuracy_label.grid(column=1, row=row, padx=10, pady=5, sticky='e')
            row += 1

            tk.Label(self, text="Current Loss:").grid(column=0, row=row, padx=10, pady=5, sticky='w')
            last_loss = "NA"
            if self.app_state.neural_net.last_loss is not None:
                last_loss = f"{self.app_state.neural_net.last_loss:.4f}"
            self.loss_label = LabelWithRefresh(self, last_loss, callback=self.recalculate_loss, initial_state=button_state)
            self.loss_label.grid(column=1, row=row, padx=10, pady=5, sticky='e')
            row += 1

    def recalculate_accuracy(self):
        self.app_state.neural_net.recalculate_accuracy(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
        self.update_ui()

    def recalculate_loss(self):
        self.app_state.neural_net.recalculate_loss(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
        self.update_ui()