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

import os
import tkinter as tk

from data.mnist_loader import MNISTModelData
from neural_net.mnist import MNISTNeuralNet
from ui.app_state import AppState
from ui.front_page.sections.neural_net_info_widget import NeuralNetInfoWidget

class NeuralNetInfo(tk.LabelFrame):
    def __init__(self, parent, app_state: AppState, on_load_model, on_load_data):
        super().__init__(parent, text="Model overview")
        self.app_state = app_state
        self.cb_on_load_model = on_load_model
        self.cb_on_load_data = on_load_data
        self.create_ui()

    def create_ui(self):
        # Option to load model (could be a file dialog or dropdown in future)
        self.load_model_button = tk.Button(self, text="Load model", command=self.on_load_model)
        self.load_model_button.pack(padx=5, pady=5, side=tk.TOP)

        if self.app_state.neural_net is None:
            self.model_status = tk.Label(self, text="No model loaded")
            self.model_status.pack(padx=5, pady=5)
        else:
            self.load_model_button.config(text="Reload model")

        load_data_button = tk.Button(self, text="Load data", command=self.on_load_data)
        load_data_button.pack(padx=5, pady=5, side=tk.TOP)
        if self.app_state.model_data is None:
            self.data_status = tk.Label(self, text="No data loaded")
            self.data_status.pack(padx=5, pady=5)
        else:
            load_data_button.config(text="Reload data")

        self.neural_net_info = NeuralNetInfoWidget(self, self.app_state)
        self.neural_net_info.pack(padx=5, pady=5)

    def update(self):
        if self.app_state.neural_net is None and self.model_status is None:
            self.model_status = tk.Label(self, text="No model loaded")
            self.model_status.pack(padx=5, pady=5)

        load_data_button = tk.Button(self, text="Load data", command=self.on_load_data)
        load_data_button.pack(padx=5, pady=5, side=tk.TOP)
        if self.app_state.model_data is None:
            self.data_status = tk.Label(self, text="No data loaded")
            self.data_status.pack(padx=5, pady=5)
        else:
            load_data_button.config(text="Reload data")

        self.neural_net_info = NeuralNetInfoWidget(self, self.app_state)
        self.neural_net_info.pack(padx=5, pady=5)

    def on_load_data(self):
        data_folder = "/projects/learning/datasets/minst"
        self.app_state.model_data = MNISTModelData(
            os.path.join(data_folder, "train-images-idx3-ubyte"),
            os.path.join(data_folder, "train-labels-idx1-ubyte"),
            os.path.join(data_folder, "t10k-images-idx3-ubyte"),
            os.path.join(data_folder, "t10k-labels-idx1-ubyte")
        )
        if self.app_state.neural_net is not None:
            self.app_state.neural_net.recalculate_loss(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
            self.app_state.neural_net.recalculate_accuracy(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
        if self.cb_on_load_data is not None:
            self.cb_on_load_data()

    def on_load_model(self):
        self.app_state.neural_net = MNISTNeuralNet()
        if self.app_state.model_data is not None:
            self.app_state.neural_net.recalculate_loss(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
            self.app_state.neural_net.recalculate_accuracy(self.app_state.model_data.test_inputs, self.app_state.model_data.test_labels)
        if self.cb_on_load_model is not None:
            self.cb_on_load_model()