plot_image.py

from PIL import Image
import matplotlib.pyplot as plt

import json
import base64
from io import BytesIO
from PIL import Image

import math

IMAGE_FACTOR = 28
MIN_PIXELS = 100 * 28 * 28
MAX_PIXELS = 16384 * 28 * 28
MAX_RATIO = 200

VIDEO_MIN_PIXELS = 128 * 28 * 28
VIDEO_MAX_PIXELS = 768 * 28 * 28
FRAME_FACTOR = 2
FPS = 2.0
FPS_MIN_FRAMES = 4
FPS_MAX_FRAMES = 768

def round_by_factor(number: int, factor: int) -> int:
    """Returns the closest integer to 'number' that is divisible by 'factor'."""
    return round(number / factor) * factor

def ceil_by_factor(number: int, factor: int) -> int:
    """Returns the smallest integer greater than or equal to 'number' that is divisible by 'factor'."""
    return math.ceil(number / factor) * factor

def floor_by_factor(number: int, factor: int) -> int:
    """Returns the largest integer less than or equal to 'number' that is divisible by 'factor'."""
    return math.floor(number / factor) * factor

def smart_resize(
    height: int, width: int, factor: int = IMAGE_FACTOR, min_pixels: int = MIN_PIXELS, max_pixels: int = MAX_PIXELS
) -> tuple[int, int]:
    """
    Rescales the image so that the following conditions are met:

    1. Both dimensions (height and width) are divisible by 'factor'.

    2. The total number of pixels is within the range ['min_pixels', 'max_pixels'].

    3. The aspect ratio of the image is maintained as closely as possible.
    """
    if max(height, width) / min(height, width) > MAX_RATIO:
        raise ValueError(
            f"absolute aspect ratio must be smaller than {MAX_RATIO}, got {max(height, width) / min(height, width)}"
        )
    h_bar = max(factor, round_by_factor(height, factor))
    w_bar = max(factor, round_by_factor(width, factor))
    if h_bar * w_bar > max_pixels:
        beta = math.sqrt((height * width) / max_pixels)
        h_bar = floor_by_factor(height / beta, factor)
        w_bar = floor_by_factor(width / beta, factor)
    elif h_bar * w_bar < min_pixels:
        beta = math.sqrt(min_pixels / (height * width))
        h_bar = ceil_by_factor(height * beta, factor)
        w_bar = ceil_by_factor(width * beta, factor)
    return h_bar, w_bar


def plot(model_output_width,
         model_output_height,
         image_path: str = './data/images/resized_image4.png',
         save_path: str = "test.png"):
    # Open the image
    img = Image.open(image_path)
    width, height = img.size
    print(f'Original coordinate: {width}, {height}')
    # Calculate the new dimensions
    new_height, new_width = smart_resize(height, width)

    new_coordinate = (int(model_output_width/new_width * width), int(model_output_height/new_height * height))

    print(f'Resized dimensions: {new_width}, {new_height}')
    print(new_coordinate)

    # Display the image
    plt.imshow(img)
    plt.scatter([new_coordinate[0]], [new_coordinate[1]], c='red', s=50)  # Mark the point with a red dot
    plt.axis('off')  # Set to 'off' to hide the axes
    plt.savefig(save_path, dpi=350, bbox_inches='tight', pad_inches=0)