fix cnn_classify

Author: previ

cnn_classifier.py

@@ -37,6 +37,8 @@ class CNNClassifier(object):
     def __init__(self, model_file, label_file, input_layer="input", output_layer="final_result", input_height=128, input_width=128, input_mean=127.5, input_std=127.5):
         self._graph = self.load_graph(model_file)
         self._labels = self.load_labels(label_file)
+        self.input_height=input_height
+        self.input_width=input_width
         input_name = "import/" + input_layer
         output_name = "import/" + output_layer
         self._input_operation = self._graph.get_operation_by_name(input_name);
@@ -88,7 +90,7 @@ def read_tensor_from_image_file(self, file_name, input_height=299, input_width=2
 
         float_caster = tf.cast(image_reader, tf.float32)
         dims_expander = tf.expand_dims(float_caster, 0);
-        resized = tf.image.resize_bilinear(dims_expander, [input_height, input_width])
+        resized = tf.image.resize_bilinear(dims_expander, [self.input_height, self.input_width])
         normalized = tf.divide(tf.subtract(resized, [input_mean]), [input_std])
         sess = tf.Session()
 
@@ -111,21 +113,15 @@ def load_labels(self, label_file):
     def classify_image(self,
                        image_file_or_mat,
                        top_results=3):
-        s_t = time.time()
         t = None
         if type(image_file_or_mat) == str:
             t = self.read_tensor_from_image_file(file_name=image_file_or_mat)
         else:
             t = self.read_tensor_from_image_mat(image_file_or_mat)
 
-        #logging.info( "time.norm: " + str(time.time() - s_t))
-        s_t = time.time()
-
         results = self._session.run(self._output_operation.outputs[0],
                                         {self._input_operation.outputs[0]: t})
 
-        #logging.info( "time.cls: " + str(time.time() - s_t))
-
         top_results = min(top_results, len(self._labels))
         results = np.squeeze(results)
         results_idx = np.argpartition(results, -top_results)[-top_results:]

cnn_models/models.json

@@ -1 +1 @@
-{"test_model_1": {"status": 1, "image_width": "128", "image_height": "128", "output_layer": "final_result"}, "test_model_2": {"status": 1, "image_width": "128", "image_height": "128", "output_layer": "final_result"}}
+{}

test/cnn_test.py

@@ -37,14 +37,12 @@ def test_train_set_1(self):
             time.sleep(1)
         self.assertTrue(cnn.get_models().get(name).get("status") == 1.0)
 
-        name="test_model_1"
         cnn = cnn_manager.CNNManager.get_instance()
         mod = cnn.load_model(name)
         result = mod.classify_image("photos/DSC86.jpg")
         print("result: " + str(result))
-        self.assertTrue(result["kiwi"] == 1.0)
+        self.assertTrue(result[0][0] == "kiwi" and result[0][1] == 1.0)
 
-        name="test_model_1"
         cnn = cnn_manager.CNNManager.get_instance()
         cnn.delete_model(name)
         self.assertTrue(cnn.get_models().get(name) is None)
@@ -72,7 +70,7 @@ def test_train_set_2(self):
         mod = cnn.load_model(name)
         result = mod.classify_image("photos/DSC86.jpg")
         print("result: " + str(result))
-        self.assertTrue(result["kiwi"] >= 0.9)
+        self.assertTrue(result[0][0] == "kiwi" and result[0][1] > 0.9)
 
         cnn = cnn_manager.CNNManager.get_instance()
         cnn.delete_model(name)