46 lines
1.2 KiB
Python
46 lines
1.2 KiB
Python
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import tensorflow as tf
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import sys
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import time
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import cv2
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import numpy as np
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import math
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import common
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import config
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import model
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import csv
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model=model.model(config.input_model)
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checkpoint=tf.train.Checkpoint(model=model)
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checkpoint.restore(tf.train.latest_checkpoint("./training/"))
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print("filename,center_x_mm,center_y_mm,semi_axes_a_mm,semi_axes_b_mm,angle_rad")
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with open("test_set.csv", newline='') as csvfile:
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lignes=csv.reader(csvfile, delimiter=',')
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for ligne in lignes:
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img=cv2.imread(config.dir_images_test+ligne[0])
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if img is None:
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continue
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mm_pixel=float(ligne[1])
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H, W, C=img.shape
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img=cv2.resize(img, (config.largeur, config.hauteur))
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img=np.array(img, dtype=np.float32)/255
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img=np.expand_dims(img[:, :, 0], axis=-1)
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predictions=model(np.array([img]))
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x, y, grand_axe, petit_axe, angle=predictions[0]
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x=float(x*W*mm_pixel)
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y=float(y*W*mm_pixel)
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axis_x=float(grand_axe*W*mm_pixel/2)
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axis_y=float(petit_axe*W*mm_pixel/2)
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r=np.pi
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r_2=r/2
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if angle>=0.5:
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angle=angle*r-r_2
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else:
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angle=angle*r+r_2
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print("{},{:f},{:f},{:f},{:f},{:f}".format(ligne[0], x, y, axis_x, axis_y, angle))
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