#! /usr/bin/env python
# coding: utf-8
import os, sys
import numpy as np
import cv2 as cv
import mxnet as mx
from mxnet.model import BatchEndParam
sys.path.insert(0, os.path.dirname(os.path.dirname(__file__)))
from eval.evaluator import EvalParams, Evaluator
from logger.logger_v1 import LogHandler
logging = LogHandler()
import utils.cv_show as CVShow
def cv_save_lm_rets(datas, predi, labeli, prefix, num_count=0):
if isinstance(datas, mx.nd.NDArray):
datas = datas.as_in_context(mx.cpu()).asnumpy()
if isinstance(predi, mx.nd.NDArray):
predi = predi.as_in_context(mx.cpu()).asnumpy()
if isinstance(labeli, mx.nd.NDArray):
labeli = labeli.as_in_context(mx.cpu()).asnumpy()
images = CVShow.cv_draw_batch_points(datas, predi * 64, color=(255, 0, 0))
images = np.stack([image.get().transpose((2, 0, 1)) for image in images],
axis=0)
images = CVShow.cv_draw_batch_points(images,
labeli,
normalized=False,
color=(0, 0, 255))
for image in images:
image_file = prefix + f"{num_count:06d}.jpg"
image = cv.cvtColor(image, cv.COLOR_RGB2BGR)
def __init__(self, name='MobileNetV20Transform', logger=LogHandler()):
super(MobileNetV20Transform, self).__init__(name)
self.name = name
self.logging = logger