Fixing SSD and SSDlite docs (#3896)

docs/source/models.rst

@@ -388,6 +388,7 @@ architectures for detection:
 - `Mask R-CNN <https://arxiv.org/abs/1703.06870>`_
 - `RetinaNet <https://arxiv.org/abs/1708.02002>`_
 - `SSD <https://arxiv.org/abs/1512.02325>`_
+- `SSDlite <https://arxiv.org/abs/1801.04381>`_
 
 The pre-trained models for detection, instance segmentation and
 keypoint detection are initialized with the classification models
@@ -475,9 +476,9 @@ Runtime characteristics
 The implementations of the models for object detection, instance segmentation
 and keypoint detection are efficient.
 
-In the following table, we use 8 V100 GPUs, with CUDA 10.0 and CUDNN 7.4 to
-report the results. During training, we use a batch size of 2 per GPU, and
-during testing a batch size of 1 is used.
+In the following table, we use 8 GPUs to report the results. During training,
+we use a batch size of 2 per GPU for all models except SSD which uses 4
+and SSDlite which uses 24. During testing a batch size  of 1 is used.
 
 For test time, we report the time for the model evaluation and postprocessing
 (including mask pasting in image), but not the time for computing the

gallery/plot_visualization_utils.py

@@ -10,7 +10,6 @@ visualizing images, bounding boxes, and segmentation masks.
 
 import torch
 import numpy as np
-import scipy.misc
 import matplotlib.pyplot as plt
 
 import torchvision.transforms.functional as F
@@ -68,7 +67,9 @@ show(result)
 # models.  Here is demo with a Faster R-CNN model loaded from
 # :func:`~torchvision.models.detection.fasterrcnn_resnet50_fpn`
 # model. You can also try using a RetinaNet with
-# :func:`~torchvision.models.detection.retinanet_resnet50_fpn`. For more details
+# :func:`~torchvision.models.detection.retinanet_resnet50_fpn`, an SSDlite with
+# :func:`~torchvision.models.detection.ssdlite320_mobilenet_v3_large` or an SSD with
+# :func:`~torchvision.models.detection.ssd300_vgg16`. For more details
 # on the output of such models, you may refer to :ref:`instance_seg_output`.
 
 from torchvision.models.detection import fasterrcnn_resnet50_fpn