# DeepGeo Extension :: Mask R-CNN
- Easy Deep Learning
- Copyright (c) 2019 [InfoLab](http://infolab.kunsan.ac.kr) ([Donggun LEE](http://duration.digimoon.net))
- How to install
```bash
pip install deepgeo_ext_maskrcnn
```
- other version
```basha
# 0.0.1
pip install deepgeo_ext_maskrcnn==0.0.1
```
- requirement
- Python 3.6
```bash
pip install deepgeo
```
- How to use
```python
import deepgeo
engine = deepgeo.Engine()
engine.add_model('maskrcnn_mscoco','maskrcnn','D:/default_config.json')
image = deepgeo.Image.Image("image.jpg","D:/Project")
image = engine.detect('maskrcnn_mscoco', image)
image.draw_annotations(image.get_annotation())
image.save("D:/","test","PNG")
```
- default_config.json
```json
{
"BACKBONE": "resnet101",
"BACKBONE_STRIDES": [
4,
8,
16,
32,
64
],
"BATCH_SIZE": 1,
"BBOX_STD_DEV": [0.1, 0.1, 0.2, 0.2],
"CATEGORY": [
"bg",
"person",
"bicycle",
"car",
"motorcycle",
"airplane",
"bus",
"train",
"truck",
"boat",
"traffic_light",
"fire_hydrant",
"stop_sign",
"parking_meter",
"bench",
"bird",
"cat",
"dog",
"horse",
"sheep",
"cow",
"elephant",
"bear",
"zebra",
"giraffe",
"backpack",
"umbrella",
"handbag",
"tie",
"suitcase",
"frisbee",
"skis",
"snowboard",
"sports_ball",
"kite",
"baseball_bat",
"baseball_glove",
"skateboard",
"surfboard",
"tennis_racket",
"bottle",
"wine_glass",
"cup",
"fork",
"knife",
"spoon",
"bowl",
"banana",
"apple",
"sandwich",
"orange",
"broccoli",
"carrot",
"hot_dog",
"pizza",
"donut",
"cake",
"chair",
"couch",
"potted_plant",
"bed",
"dining_table",
"toilet",
"tv",
"laptop",
"mouse",
"remote",
"keyboard",
"cell_phone",
"microwave",
"oven",
"toaster",
"sink",
"refrigerator",
"book",
"clock",
"vase",
"scissors",
"teddy_bear",
"hair_drier",
"toothbrush"
],
"COMPUTE_BACKBONE_SHAPE": null,
"DETECTION_MAX_INSTANCES": 100,
"DETECTION_MIN_CONFIDENCE": 0.7,
"DETECTION_NMS_THRESHOLD": 0.3,
"EPOCHS": 1,
"FPN_CLASSIF_FC_LAYERS_SIZE": 1024,
"GPU_COUNT": 1,
"GRADIENT_CLIP_NORM": 5.0,
"IMAGES_PER_GPU": 1,
"IMAGE_CHANNEL_COUNT": 3,
"IMAGE_MAX_DIM": 1024,
"IMAGE_META_SIZE": 14,
"IMAGE_MIN_DIM": 800,
"IMAGE_MIN_SCALE": 0,
"IMAGE_PATH": "image",
"IMAGE_RESIZE_MODE": "square",
"IMAGE_SHAPE": null,
"LAYERS": "all",
"LEARNING_MOMENTUM": 0.9,
"LEARNING_RATE": 0.001,
"LOSS_WEIGHTS": {
"mrcnn_bbox_loss": 1.0,
"mrcnn_class_loss": 1.0,
"mrcnn_mask_loss": 1.0,
"rpn_bbox_loss": 1.0,
"rpn_class_loss": 1.0
},
"MASK_POOL_SIZE": 14,
"MASK_SHAPE": [
28,
28
],
"MAX_GT_INSTANCES": 100,
"MEAN_PIXEL": [123.7, 116.8, 103.9],
"MEMO": "",
"MINI_MASK_SHAPE": [
56,
56
],
"MODEL_FILE_NAME": "mask_rcnn_coco.h5",
"MODEL_PATH":"model",
"MODEL_URI":"",
"NAME": "MASK_RCNN",
"NUM_CLASSES": 80,
"POOL_SIZE": 7,
"POST_NMS_ROIS_INFERENCE": 1000,
"POST_NMS_ROIS_TRAINING": 2000,
"PRE_NMS_LIMIT": 6000,
"RESULT_TEST_NUM": 100,
"ROI_POSITIVE_RATIO": 0.33,
"RPN_ANCHOR_RATIOS": [
0.5,
1,
2
],
"RPN_ANCHOR_SCALES": [
32,
64,
128,
256,
512
],
"RPN_ANCHOR_STRIDE": 1,
"RPN_BBOX_STD_DEV": [0.1,0.1,0.2,0.2],
"RPN_NMS_THRESHOLD": 0.7,
"RPN_TRAIN_ANCHORS_PER_IMAGE": 256,
"STEPS_PER_EPOCH": 1000,
"TOP_DOWN_PYRAMID_SIZE": 256,
"TRAIN_BN": false,
"TRAIN_ROIS_PER_IMAGE": 200,
"USE_MINI_MASK": true,
"USE_RPN_ROIS": true,
"VALIDATION_STEPS": 50,
"VERSION": "",
"WEIGHT_DECAY": 0.0001
}
```
