update docs; convert box to float in generic evaluator

Summary: Pull Request resolved: fairinternal/detectron2#327

Differential Revision: D18503824

Pulled By: ppwwyyxx

fbshipit-source-id: 4a75fc93f6efa75af31107f0b152ac9a683e9807

GETTING_STARTED.md

@@ -20,11 +20,13 @@ For more advanced tutorials, refer to our [documentation](https://detectron2.rea
 ```
 python demo/demo.py --config-file configs/COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x.yaml \
   --input input1.jpg input2.jpg \
+	[--other-options]
   --opts MODEL.WEIGHTS detectron2://COCO-InstanceSegmentation/mask_rcnn_R_50_FPN_3x/137849600/model_final_f10217.pkl
 ```
 The configs are made for training, therefore we need to specify `MODEL.WEIGHTS` to a model from model zoo for evaluation.
 This command will run the inference and show visualizations in an OpenCV window.
 
+For details of the command line arguments, see `demo.py -h`. Some common ones are:
 * To run __on your webcam__, replace `--input files` with `--webcam`.
 * To run __on a video__, replace `--input files` with `--video-input video.mp4`.
 * To run __on cpu__, add `MODEL.DEVICE cpu` after `--opts`.

INSTALL.md

@@ -28,7 +28,7 @@ python setup.py build develop
 # MACOSX_DEPLOYMENT_TARGET=10.9 CC=clang CXX=clang++ python setup.py build develop
 
 # or, as an alternative to `setup.py`, do
-# pip install .
+# pip install [--editable] .
 ```
 Note: you may need to rebuild detectron2 after reinstalling a different build of PyTorch.
 
@@ -61,4 +61,8 @@ Note: you may need to rebuild detectron2 after reinstalling a different build of
 	```
 	print valid outputs at the time you build detectron2.
 
-+ "invalid device function": you build detectron2 with one version of CUDA but run it with a different version.
++ "invalid device function": two possibilities:
+  * You build detectron2 with one version of CUDA but run it with a different version.
+	* Detectron2 is not built with the correct compute compability for the GPU model.
+	  The compute compability defaults to match the GPU found on the machine,
+		and can be controlled by `TORCH_CUDA_ARCH_LIST` environment variable during installation.

demo/demo.py

@@ -55,7 +55,7 @@ def get_parser():
     )
     parser.add_argument(
         "--opts",
-        help="Modify model config options using the command-line",
+        help="Modify config options using the command-line 'KEY VALUE' pairs",
         default=[],
         nargs=argparse.REMAINDER,
     )

detectron2/data/catalog.py

@@ -35,6 +35,7 @@ def register(name, func):
             func (callable): a callable which takes no arguments and returns a list of dicts.
         """
         assert callable(func), "You must register a function with `DatasetCatalog.register`!"
+        assert name not in DatasetCatalog._REGISTERED, "Dataset '{}' is already registered!".format(name)
         DatasetCatalog._REGISTERED[name] = func
 
     @staticmethod

detectron2/data/datasets/coco.py

@@ -352,7 +352,7 @@ def convert_to_coco_dict(dataset_name):
             #   "id" field must start with 1
             coco_annotation["id"] = len(coco_annotations) + 1
             coco_annotation["image_id"] = image_dict["image_id"]
-            coco_annotation["bbox"] = bbox
+            coco_annotation["bbox"] = [round(float(x), 3) for x in bbox]
             coco_annotation["area"] = area
             coco_annotation["category_id"] = annotation["category_id"]
             coco_annotation["iscrowd"] = annotation.get("iscrowd", 0)

detectron2/engine/defaults.py

@@ -135,6 +135,10 @@ class DefaultPredictor:
     The predictor takes an BGR image, resizes it to the specified resolution,
     runs the model and produces a dict of predictions.
 
+    This predictor takes care of model loading and input preprocessing for you.
+    If you'd like to do anything more fancy, please refer to its source code
+    as examples to build and use the model manually.
+
     Attributes:
         metadata (Metadata): the metadata of the underlying dataset, obtained from
             cfg.DATASETS.TEST.