[add] backbone and detector

model/backbone/densenet.py

@@ -0,0 +1,15 @@
+from torch import nn
+from torchvision.models.detection.backbone_utils import _resnet_fpn_extractor, resnet_fpn_backbone, BackboneWithFPN
+
+class DenseNet(nn.Module):
+    def __init__(self, num_classes):     # @Thuan: Add argumentation in __init__
+        super(DenseNet, self).__init__()
+        # @Thuan: Initiation model here
+
+        # End of model initiation
+
+    def forward(self, x):
+        # @Thuan: Feedforward step here
+
+        return x    # End of feedforward function
+

model/detector/fasterRCNN.py

@@ -0,0 +1,18 @@
+import torchvision
+from torchvision.models.detection import FasterRCNN
+from torchvision.models.detection.rpn import AnchorGenerator
+
+def fasterRCNN(backbone, class_num):
+    anchor_generator = AnchorGenerator(sizes=((32, 64, 128, 256, 512),),
+                                    aspect_ratios=((0.5, 1.0, 2.0),))
+
+    roi_pooler = torchvision.ops.MultiScaleRoIAlign(featmap_names=['0'],
+                                                    output_size=7,
+                                                    sampling_ratio=2)
+
+    # put the pieces together inside a FasterRCNN model
+    model = FasterRCNN(backbone,
+                    num_classes=class_num,
+                    rpn_anchor_generator=anchor_generator,
+                    box_roi_pool=roi_pooler)
+    return model