config.sample.yml

---
### Inference Config
VIDEO_INPUT: 0                      # Input Must be OpenCV readable
ROS_INPUT: /camera/color/image_raw  # ROS Image Topic
VISUALIZE: True                     # Disable for performance increase
VIS_FPS: True                       # Draw current FPS in the top left Image corner
CPU_ONLY: False                     # CPU Placement for speed test
USE_OPTIMIZED: False                # whether to use the optimized model (only possible if transform with script)
DISCO_MODE: False                   # Secret Disco Visualization Mode
DOWNLOAD_MODEL: False               # Only for Models available at the TF model_zoo


### Testing
IMAGE_PATH: 'test_images'           # path for test_*.py test_images
LIMIT_IMAGES: None                  # if set to None, all images are used
WRITE_TIMELINE: True                # write json timeline file (slows infrence)
SAVE_RESULT: False                  # save detection results to disk
RESULT_PATH: 'test_results'         # path to save detection results
SEQ_MODELS: []                      # List of Models to sequentially test (Default all Models)


### Object_Detection
WIDTH: 600                          # OpenCV Video stream width
HEIGHT: 600                         # OpenCV Video stream height
MAX_FRAMES: 5000                    # only used if visualize==False
FPS_INTERVAL: 5                     # Interval [s] to print fps of the last interval in console
PRINT_INTERVAL: 500                 # intervall [frames] to print detections to console
PRINT_TH: 0.5                       # detection threshold for det_intervall
## speed hack
SPLIT_MODEL: True                   # Splits Model into a GPU and CPU session (currently only works for ssd_mobilenets)
MULTI_THREADING: True               # Additional Split Model Speed up through multi threading
SSD_SHAPE: 300                      # used for the split model algorithm (currently only supports ssd networks trained on 300x300 and 600x600 input)
SPLIT_NODES: ['Postprocessor/convert_scores','Postprocessor/ExpandDims_1']
                                    # hardcoded split points for ssd_mobilenet_v1
## Tracking
USE_TRACKER: False                  # Use a Tracker (deactivates mask detection)
TRACKER_FRAMES: 20                  # Number of tracked frames between detections
NUM_TRACKERS: 5                     # Max number of objects to track
## Model
OD_MODEL_NAME: 'ssd_mobilenet_v11_coco'
OD_MODEL_PATH: 'models/ssd_mobilenet_v11_coco/{}'
LABEL_PATH: 'rod/data/tf_coco_label_map.pbtxt'
NUM_CLASSES: 90


### DeepLab
ALPHA: 0.3                     # mask overlay factor (also for mask_rcnn)
BBOX: True                     # compute boundingbox in postprocessing
MINAREA: 500                   # min Pixel Area to apply bounding boxes (avoid noise)
## Model
DL_MODEL_NAME: 'deeplabv3_mnv2_pascal_train_aug_2018_01_29'
DL_MODEL_PATH: 'models/deeplabv3_mnv2_pascal_train_aug/{}'