greenhouse/libs/create_ml_io.py
enicck 31463497c8
Adds create-ml format support (#651)
* adds createMl reader & writer class

* adds getFormatMeta function to support more than two save_format

* adds CreateML read & write support

* adds format CreateML icon

* fixes negative height/width

* removes type hints

* fixes coordinate calculation

* adds unit test

* removes typehint
2020-10-02 06:56:07 -07:00

132 lines
3.7 KiB
Python

#!/usr/bin/env python
# -*- coding: utf8 -*-
import json
from pathlib import Path
from libs.constants import DEFAULT_ENCODING
import os
JSON_EXT = '.json'
ENCODE_METHOD = DEFAULT_ENCODING
class CreateMLWriter:
def __init__(self, foldername, filename, imgsize, shapes, outputfile, databasesrc='Unknown', localimgpath=None):
self.foldername = foldername
self.filename = filename
self.databasesrc = databasesrc
self.imgsize = imgsize
self.boxlist = []
self.localimgpath = localimgpath
self.verified = False
self.shapes = shapes
self.outputfile = outputfile
def write(self):
if os.path.isfile(self.outputfile):
with open(self.outputfile, "r") as file:
input_data = file.read()
outputdict = json.loads(input_data)
else:
outputdict = []
outputimagedict = {
"image": self.filename,
"annotations": []
}
for shape in self.shapes:
points = shape["points"]
x1 = points[0][0]
y1 = points[0][1]
x2 = points[1][0]
y2 = points[2][1]
height, width, x, y = self.calculate_coordinates(x1, x2, y1, y2)
shapedict = {
"label": shape["label"],
"coordinates": {
"x": x,
"y": y,
"width": width,
"height": height
}
}
outputimagedict["annotations"].append(shapedict)
# check if image already in output
exists = False
for i in range(0, len(outputdict)):
if outputdict[i]["image"] == outputimagedict["image"]:
exists = True
outputdict[i] = outputimagedict
break
if not exists:
outputdict.append(outputimagedict)
Path(self.outputfile).write_text(json.dumps(outputdict), ENCODE_METHOD)
def calculate_coordinates(self, x1, x2, y1, y2):
if x1 < x2:
xmin = x1
xmax = x2
else:
xmin = x2
xmax = x1
if y1 < y2:
ymin = y1
ymax = y2
else:
ymin = y2
ymax = y1
width = xmax - xmin
if width < 0:
width = width * -1
height = ymax - ymin
# x and y from center of rect
x = xmin + width / 2
y = ymin + height / 2
return height, width, x, y
class CreateMLReader:
def __init__(self, jsonpath, filepath):
self.jsonpath = jsonpath
self.shapes = []
self.verified = False
self.filename = filepath.split("/")[-1:][0]
try:
self.parse_json()
except ValueError:
print("JSON decoding failed")
def parse_json(self):
with open(self.jsonpath, "r") as file:
inputdata = file.read()
outputdict = json.loads(inputdata)
self.verified = True
if len(self.shapes) > 0:
self.shapes = []
for image in outputdict:
if image["image"] == self.filename:
for shape in image["annotations"]:
self.add_shape(shape["label"], shape["coordinates"])
def add_shape(self, label, bndbox):
xmin = bndbox["x"] - (bndbox["width"] / 2)
ymin = bndbox["y"] - (bndbox["height"] / 2)
xmax = bndbox["x"] + (bndbox["width"] / 2)
ymax = bndbox["y"] + (bndbox["height"] / 2)
points = [(xmin, ymin), (xmax, ymin), (xmax, ymax), (xmin, ymax)]
self.shapes.append((label, points, None, None, True))
def get_shapes(self):
return self.shapes