import pygame, torch, cv2, numpy as np
from inference import predict

def draw_digi():
    pygame.init()
    window_size = 280
    display_height = window_size+50
    screen = pygame.display.set_mode((window_size,display_height))
    pygame.display.set_caption("Draw a digit")
    clock = pygame.time.Clock()
    screen.fill((0,0,0))
    drawing = False
    prediction = None

    font = pygame.font.Font(None,36)
    while True:
        # screen.fill((0,0,0))
        for event in pygame.event.get():
            if event.type == pygame.QUIT:
                pygame.quit()
                return
            if event.type == pygame.MOUSEBUTTONDOWN:
                drawing = True
            if event.type == pygame.MOUSEBUTTONUP:
                drawing = False
                prediction = predict_digit(screen)
            if event.type == pygame.KEYDOWN:
                if event.key == pygame.K_c:
                    screen.fill((0,0,0))
                    prediction = None

            if event.type == pygame.MOUSEMOTION and drawing:
                pygame.draw.circle(screen,(255,255,255),event.pos,8)
            
        if prediction is not None:
                text = font.render(f"Prediction: {prediction}",True,(0,255,0))
                screen.blit(text,(10,window_size+10))
            
        pygame.display.flip()
        clock.tick(60)

def process_drawing(screen):
    surface = pygame.surfarray.array3d(screen)
    gray = np.dot(surface[...,:3],[0.2989,0.5870,0.1140])
    gray = np.transpose(gray,(1,0))
    gray = cv2.resize(gray,(28,28),interpolation=cv2.INTER_AREA)
    gray = gray.astype(np.float32)/255.0
    gray = (gray - 0.5)/0.5
    tensor = torch.tensor(gray,dtype=torch.float32).unsqueeze(0).unsqueeze(0)
    return tensor
def predict_digit(screen):
    image = process_drawing(screen)
    if image is None:
        return None
    return predict(image)

draw_digi()