import matplotlib.pyplot as plt
import numpy as np
import cv2


VOXEL_SIZE = 0.1
X_MIN, X_MAX = -5, 5
Y_MIN, Y_MAX = -5, 5

x_vals = np.arange(X_MIN + VOXEL_SIZE / 2, X_MAX, VOXEL_SIZE)
y_vals = np.arange(Y_MIN + VOXEL_SIZE / 2, Y_MAX, VOXEL_SIZE)

image_length = 1500


def f(x, y):
    return np.exp(-((x**2) + y**2) / 3)


X, Y = np.meshgrid(x_vals, y_vals)

Z = f(X - 2, Y) + f(X + 2, Y)
Z = (Z > 0.4).astype(np.float32)
Z *= np.random.rand(*Z.shape)

for j, x in enumerate(x_vals):
    for i, y in enumerate(y_vals):
        color = f"{hex(int(Z[i, j] * 255))[2:]}"
        if color == "0":
            color = "#003"
        else:
            color = "#" + 3 * color
        plt.fill([x - VOXEL_SIZE/2, x + VOXEL_SIZE/2, x + VOXEL_SIZE/2, x - VOXEL_SIZE/2],
                 [y - VOXEL_SIZE/2, y - VOXEL_SIZE/2, y + VOXEL_SIZE/2, y + VOXEL_SIZE/2], color=color)

nb_cams = 32
cam_poses = np.array(
    [[6 * np.cos(theta), 6 * np.sin(theta)]
     for theta in np.linspace(0, 2 * np.pi, nb_cams, endpoint=False)]
)
cam_rots = np.linspace(np.pi, 3 * np.pi, nb_cams, endpoint=False)
cam2world_projs = np.array(
    [
        [[np.cos(theta), -np.sin(theta), cam_pose[0]],
         [np.sin(theta), np.cos(theta), cam_pose[1]],
         [0, 0, 1]]
        for theta, cam_pose in zip(cam_rots, cam_poses)
    ]
)

for i in range(nb_cams):
    x = np.array([[0, 0, 1], [0.5, -0.2, 1], [0.5, 0.2, 1], [0, 0, 1]])
    x = cam2world_projs[i] @ x.T
    plt.plot(cam_poses[i][0], cam_poses[i][1], "ro")
    plt.text(cam_poses[i][0], cam_poses[i][1], str(i))
    plt.plot(x[0, :], x[1, :], "r-")

plt.xlim(-7, 7)
plt.ylim(-7, 7)
plt.axis("equal")
plt.axis("off")
plt.savefig("data/peanut/peanut_cams.png", dpi=300,
            bbox_inches="tight", pad_inches=0, transparent=True)
plt.close()

# draw 1d image of the scene for each camera
for i in range(nb_cams):

    # sort pixels by distance to camera
    cam_pose = cam_poses[i]
    pixels_dist = np.linalg.norm(
        np.array([X.flatten(), Y.flatten()]).T - cam_pose, axis=1)
    pixels_sort = np.argsort(pixels_dist)[::-1]

    x0 = -1
    x1 = 1

    img = np.zeros((100, image_length, 3), dtype=np.uint8)
    mask = np.zeros((100, image_length, 3), dtype=np.uint8)

    for j in pixels_sort:
        x, y = X.flatten()[j], Y.flatten()[j]
        color = int(Z.flatten()[j] * 255)
        if color == 0:
            continue

        RT = np.linalg.inv(cam2world_projs[i])[:-1, :]
        px = np.array([[x - VOXEL_SIZE/2, y - VOXEL_SIZE/2, 1],
                       [x + VOXEL_SIZE/2, y - VOXEL_SIZE/2, 1],
                       [x + VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1],
                       [x - VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1]])
        px = RT @ px.T
        px /= px[0, :]
        px += np.array([[0], [1.0]])
        px *= 0.5 * np.array([[1], [image_length]])

        x0 = px[1, :].min()
        x1 = px[1, :].max()

        img[:, int(x0):int(x1), :] = np.array(
            3 * [color], dtype=np.uint8)
        mask[:, int(x0):int(x1), :] = np.array([255, 255, 255], dtype=np.uint8)

    # x, y = X_MIN + 27 * VOXEL_SIZE, Y_MIN + 66 * VOXEL_SIZE
    # RT = np.linalg.inv(cam2world_projs[i])[:-1, :]
    # px = np.array([[x + VOXEL_SIZE/2, y + VOXEL_SIZE/2, 1],
    #                [x, y, 1],
    #                [x + VOXEL_SIZE, y, 1],
    #                [x + VOXEL_SIZE, y + VOXEL_SIZE, 1],
    #                [x, y + VOXEL_SIZE, 1]])
    # px = RT @ px.T
    # px /= px[0, :]
    # px += np.array([[0], [1.0]])
    # px *= 0.5 * np.array([[1], [image_length]])

    # img[48:52, int(px[1, 0]-1):int(px[1, 0]+1), :] = np.array([255, 0, 0], dtype=np.uint8)
    # img[48:52, int(px[1, 1]-1):int(px[1, 1]+1), :] = np.array([255, 255, 0], dtype=np.uint8)
    # img[48:52, int(px[1, 2]-1):int(px[1, 2]+1), :] = np.array([0, 255, 255], dtype=np.uint8)
    # img[48:52, int(px[1, 3]-1):int(px[1, 3]+1), :] = np.array([255, 0, 255], dtype=np.uint8)
    # img[48:52, int(px[1, 4]-1):int(px[1, 4]+1), :] = np.array([0, 255, 0], dtype=np.uint8)

    cv2.imwrite(f"data/peanut/images/Image{i:04}.png", img)
    cv2.imwrite(f"data/peanut/masks/Image{i:04}.png", mask)