import argparse
import logging as log

import numpy as np
from keras.models import load_model

from prepare_data import loadDataset,Sample
from analyzer.epoint import EPoint
from analyzer.corners import Corners
import config as cfg


parser=argparse.ArgumentParser()
parser.add_argument("model")
parser.add_argument("data")
args=parser.parse_args()

model=load_model(args.model)

log.info("loading data...")
with np.load(args.data) as data:
	trainImages=data["trainImages"]
	trainLabels=data["trainLabels"]
	testImages=data["testImages"]
	testLabels=data["testLabels"]
log.info("done")

log.info(model.evaluate(testImages.reshape((-1,224,224,1)),testLabels))

for img in testImages:
	label=model.predict(np.reshape(img,(1,224,224,1)))
	print(label)
	points=[]
	for i in range(4):
		points.append(EPoint((label[0][i*2]+1)*112,(label[0][i*2+1]+1)*112))
	corners=Corners(points)
	sample=Sample(np.uint8(img*255),corners)
	sample.show()