import argparse

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


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

model=load_model(args.model)

print("loading data...")
((trainImages,trainLabels),(testImages,testLabels))=loadDataset(args.data_dir)
print("done")

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],label[0][i*2+1]))
	corners=Corners(points)
	sample=Sample(np.uint8(img),corners)
	sample.show()