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hepesu · Mar 17, 2018 · 2ca3e5c · 2ca3e5c
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diff --git a/figs/3d_1.jpg b/figs/3d_1.jpg
diff --git a/figs/3d_12x.jpg b/figs/3d_12x.jpg
diff --git a/figs/3d_2.jpg b/figs/3d_2.jpg
diff --git a/figs/curve.jpg b/figs/curve.jpg
diff --git a/figs/l1.jpg b/figs/l1.jpg
diff --git a/figs/l1_2x.jpg b/figs/l1_2x.jpg
diff --git a/figs/one_pixel_gap.jpg b/figs/one_pixel_gap.jpg
diff --git a/figs/overview.jpg b/figs/overview.jpg
diff --git a/predict.py b/predict.py
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+import os
+
+# Try running on CPU
+os.environ['CUDA_VISIBLE_DEVICES'] = '-1'
+
+import numpy as np
+import cv2
+from keras.models import load_model
+
+MODEL_NAME = 'model.h5'
+model = load_model(MODEL_NAME)
+
+for root, dirs, files in os.walk('data/predict', topdown=False):
+    for name in files:
+        print(os.path.join(root, name))
+
+        im = cv2.imread(os.path.join(root, name))
+        im_gray = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+
+        im_predict = im_gray.reshape((1, im_gray.shape[0], im_gray.shape[1], 1))
+        im_predict = (im_predict.astype(np.float32) / 255. - 0.5) * 2
+
+        result = model.predict(im_predict)
+
+        im_res = result.reshape((result.shape[1], result.shape[2]))
+        im_res = (im_res * 0.5 + 0.5) * 255
+
+        cv2.imwrite(os.path.join('data/result', name), im_res)