from scene.cameras import Camera
import numpy as np
from utils.general_utils import PILtoTorch
from utils.graphics_utils import fov2focal

def loadCam(args, id, cam_info, resolution_scale):
    orig_w, orig_h = cam_info.image.size

    if args.resolution in [1, 2, 4, 8]:
        resolution = round(orig_w/(resolution_scale * args.resolution)), round(orig_h/(resolution_scale * args.resolution))
    else:  # should be a type that converts to float
        global_down = orig_w/args.resolution
        scale = float(global_down) * float(resolution_scale)
        resolution = (int(orig_w / scale), int(orig_h / scale))

    resized_image_rgb = PILtoTorch(cam_info.image, resolution)

    gt_image = resized_image_rgb[:3, ...]
    loaded_mask = None

    if resized_image_rgb.shape[1] == 4:
        loaded_mask = resized_image_rgb[3:4, ...]

    return Camera(colmap_id=cam_info.uid, R=cam_info.R, T=cam_info.T, 
                  FoVx=cam_info.FovX, FoVy=cam_info.FovY, 
                  image=gt_image, gt_alpha_mask=loaded_mask,
                  image_name=cam_info.image_name, uid=id)

def cameraList_from_camInfos(cam_infos, resolution_scale, args):
    camera_list = []

    for id, c in enumerate(cam_infos):
        camera_list.append(loadCam(args, id, c, resolution_scale))

    return camera_list

def camera_to_JSON(id, camera : Camera):
    Rt = np.zeros((4, 4))
    Rt[:3, :3] = camera.R.transpose()
    Rt[:3, 3] = camera.T
    Rt[3, 3] = 1.0

    W2C = np.linalg.inv(Rt)
    pos = W2C[:3, 3]
    rot = W2C[:3, :3]
    serializable_array_2d = [x.tolist() for x in rot]
    camera_entry = {
        'id' : id,
        'img_name' : camera.image_name,
        'width' : camera.width,
        'height' : camera.height,
        'position': pos.tolist(),
        'rotation': serializable_array_2d,
        'fy' : fov2focal(camera.FovY, camera.height),
        'fx' : fov2focal(camera.FovX, camera.width)
    }
    return camera_entry