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run_demo.py

+"""
+MIT License
+
+Copyright (c) 2019 Sadeep Jayasumana
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.
+"""
+import torch
+
+from crfasrnn import util
+from crfasrnn.crfasrnn_model import CrfRnnNet
+
+
+def main():
+    input_file = "image.jpg"
+    output_file = "labels.png"
+
+    # Read the image
+    img_data, img_h, img_w, size = util.get_preprocessed_image(input_file)
+
+    # Download the model from https://tinyurl.com/crfasrnn-weights-pth
+    saved_weights_path = "crfasrnn_weights.pth"
+
+    model = CrfRnnNet()
+    model.load_state_dict(torch.load(saved_weights_path))
+    model.eval()
+    out = model.forward(torch.from_numpy(img_data))
+
+    probs = out.detach().numpy()[0]
+    label_im = util.get_label_image(probs, img_h, img_w, size)
+    label_im.save(output_file)
+
+
+if __name__ == "__main__":
+    main()