Parsing content in txt in Python to json file

      In instant-ngp, the transforms.json file can be automatically generated by calling scripts/colmap2nerf.py, that is, the camera parameters, but sometimes these parameters are obtained from the camera itself, in order to automatically generate instant-ngp for each camera parameter information, that is, the txt content The supported transforms.json file is implemented in python here.

      The format of the txt content of each camera is as follows: the first three lines are camera internal parameters, including fx, fy, cx, cy; the last three lines are camera external parameters, which are Rt

8242.163473484103 0 2576.928611903816 0
0 8242.163473484103 1733.503691370957 0
0 0 1 0
2.044289726145588e-004 -0.2587487517264626 -0.9659446369688031 27.59432346095996
-0.9993063898830017 -3.602307923217642e-002 9.438056030485108e-003 -0.6400803719560595
-3.723838540803551e-002 0.9652727185840433 -0.2585766451355823 35.62807466319453

      The python implementation is as follows:

import os
import json

def get_dir_list(path):
    dir_list = []
    for x in os.listdir(path):
        if x.endswith(".txt"):
            dir_list.append(path+"/"+x)

    return dir_list

def vec_to_matrix(els):
    matrix = [
        [
            els[0][0],
            els[0][1],
            els[0][2],
            els[0][3]
        ],
        [
            els[1][0],
            els[1][1],
            els[1][2],
            els[1][3]
        ],
        [
            els[2][0],
            els[2][1],
            els[2][2],
            els[2][3],
        ],
        [
            0.0,
            0.0,
            0.0,
            1.0
        ]
    ]

    return matrix

def get_image_name(txt_name, img_suffix_name):
    pos = txt_name.rfind("/")
    name = txt_name[pos+1:]
    name = name.replace("txt", img_suffix_name)
    
    return "images/" + name

def write_to_json(dir_list, out_file, img_suffix_name):
    out = {
        "frames": [],
    }

    for x in dir_list:
        with open(os.path.join(x), "r") as f:
            els = [] # 6*4
            for line in f:
                if line[0] == "#":
                    continue

                tmp = []
                for v in line.split(" "):
                    tmp.append(v.replace("\n", "")) # remove line breaks(\n) at the end of the line
                ret = [float(ele) for ele in tmp] # str to float
                els.append(ret)

            if len(els) != 6:
                print(f"Error: the number of rows that are not supported:{len(els)}")
                raise

            # camera intrinsics
            fl_x = els[0][0]
            fl_y = els[1][1]
            cx = els[0][2]
            cy = els[1][2]

            # camera extrinsics: R t
            transform_matrix = vec_to_matrix(els[3:6])

            image_name = get_image_name(x, img_suffix_name)

            frame = {"file_path":image_name,"fl_x":fl_x,"fl_y":fl_y,"cx":cx,"cy":cy,"transform_matrix":transform_matrix}
            out["frames"].append(frame)

    with open(out_file, "w") as f:
        json.dump(out, f, indent=2)

if __name__ == "__main__":
    dir_list = get_dir_list("test_data/txt")
    #print(f"dir_list:\n\t{dir_list}")

    write_to_json(dir_list, "test_data/txt/transforms.json", "png")
    print("test finish")

      The result after execution is shown in the figure below:

      GitHub：https://github.com/fengbingchun/Python_Test