Add darknet code dependences, base detection modele and make models c…

…ompatiable with singa-auto

examples/models/image_object_detection/food101.py

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+from singa_auto.darknet.food_objection_base_model import FoodDetectionBase
+from keras.applications.xception import Xception
+
+
+class FoodDetection101(FoodDetectionBase):
+
+    def __init__(self, **knobs):
+
+        super().__init__(clf_model_class_name=Xception, **knobs)
+
+        # pre config
+        self.classes = 101
+        self.image_size = 299
+
+        # preload files
+        self.yolo_cfg_name = "yolov3-food.cfg"
+        self.yolo_weight_name = "yolov3-food_final.weights"
+        self.food_name = "food.names"
+
+        # this is the model file downloaded from internet,
+        # can choose download locally and upload , or download from server
+        # if download at server side, leave it to none
+        self.preload_clf_model_weights_name = None
+
+        # this is the trained model
+        self.trained_clf_model_weights_name = "xception-F101-0.85.h5"
+
+        self._npy_index_name = "food101.npy"

examples/models/image_object_detection/food172.py

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+from keras.applications.xception import Xception
+from singa_auto.darknet.food_objection_base_model import FoodDetectionBase
+
+
+class FoodDetection172(FoodDetectionBase):
+
+    def __init__(self, **knobs):
+        super().__init__(clf_model_class_name=Xception, **knobs)
+
+        # pre config
+        self.classes = 172
+        self.image_size = 299
+
+        # preload files
+        self.yolo_cfg_name = "yolov3-food.cfg"
+        self.yolo_weight_name = "yolov3-food_final.weights"
+        self.food_name = "food.names"
+
+        # this is the model file downloaded from internet,
+        # can choose download locally and upload , or download from server
+        # if download at server side, leave it to none
+        self.preload_clf_model_weights_name = None
+
+        # this is the trained model
+        self.trained_clf_model_weights_name = "xception-800_F172-0.86.h5"
+
+        self._npy_index_name = "food172.npy"

examples/models/image_object_detection/food231.py

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+from keras.applications.xception import Xception
+from singa_auto.darknet.food_objection_base_model import FoodDetectionBase
+
+
+class FoodDetection231(FoodDetectionBase):
+
+    def __init__(self, **knobs):
+        super().__init__(clf_model_class_name=Xception, **knobs)
+
+        # pre config
+        self.classes = 231
+        self.image_size = 299
+
+        # preload files
+        self.yolo_cfg_name = "yolov3-food.cfg"
+        self.yolo_weight_name = "yolov3-food_final.weights"
+        self.food_name = "food.names"
+
+        # this is the model file downloaded from internet,
+        # can choose download locally and upload , or download from server
+        # if download at server side, leave it to none
+        self.preload_clf_model_weights_name = None
+
+        # this is the trained model
+        self.trained_clf_model_weights_name = "xception-food231-0-15-0.82.h5"
+
+        self._npy_index_name = "food231.npy"

examples/models/image_object_detection/food256.py

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+from keras.applications.inception_resnet_v2 import InceptionResNetV2
+from singa_auto.darknet.food_objection_base_model import FoodDetectionBase
+
+
+class FoodDetection256(FoodDetectionBase):
+
+    def __init__(self, **knobs):
+        super().__init__(clf_model_class_name=InceptionResNetV2, **knobs)
+
+        # pre config
+        self.classes = 256
+        self.image_size = 299
+
+        # preload files
+        self.yolo_cfg_name = "yolov3-food.cfg"
+        self.yolo_weight_name = "yolov3-food_final.weights"
+        self.food_name = "food.names"
+
+        # this is the model file downloaded from internet,
+        # can choose download locally and upload , or download from server
+        # if download at server side, leave it to none
+        self.preload_clf_model_weights_name = "inception_resnet_v2_weights_tf_dim_ordering_tf_kernels.h5"
+
+        # this is the trained model
+        self.trained_clf_model_weights_name = "inceptionresnet-U256-0.73.h5"
+
+        self._npy_index_name = "uec256.npy"

examples/models/image_object_detection/food_55.py

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+from keras.applications.inception_resnet_v2 import InceptionResNetV2
+from singa_auto.darknet.food_objection_base_model import FoodDetectionBase
+
+
+class FoodDetection55(FoodDetectionBase):
+
+    def __init__(self, **knobs):
+        super().__init__(clf_model_class_name=InceptionResNetV2, **knobs)
+
+        # pre config
+        self.classes = 55
+        self.image_size = 299
+
+        # preload files
+        self.yolo_cfg_name = "yolov3-food.cfg"
+        self.yolo_weight_name = "yolov3-food_final.weights"
+        self.food_name = "food.names"
+
+        # this is the model file downloaded from internet,
+        # can choose download locally and upload , or download from server
+        # if download at server side, leave it to none
+        self.preload_clf_model_weights_name = "inception_resnet_v2_weights_tf_dim_ordering_tf_kernels.h5"
+
+        # this is the trained model
+        self.trained_clf_model_weights_name = "inceptionresnet-FC55-0.86.h5"
+
+        self._npy_index_name = "food55.npy"