Initial commit

Tensorflow/concours_foetus/result.py

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