How can I run the model on my own dataset?

[kurdt23]

I have my own image dataset and I don't understand where/how I can make key point masks for images. Can you explain the process to prepare the own dataset and then run the model, please? I'll be waiting your answer.

[htcr]

Hi, does your dataset contain ground-truth graphs? You can process that graph into the same format as used in this codebase, then it shall generate keypoint masks for you.

[htcr]

For example, you can refer to the generate_labels.py under cityscales dir. From line 82, it reads the GT graph - and it reveals the gt graph format, basically an adjacency list of vertices.

[kurdt23]

Unfortunately my dataset does not contain ground-truth graphs. I have only satellite images of 512x512 roads with different magnification in tif format. I attach some examples of these images. Can you please help me, how can I get ground-truth graphs from my images?

[htcr]

Ok, if you were trying to re-train/fine-tune on your dataset, you do need ground-truth graph. Otherwise if you just want to run our checkpoint on some images, you can just follow the inference instruction in README.

[kurdt23]

Thank you! I have checkpoints on City scale and SpaceNet datasets, I'll try some of them on my images.

[kurdt23]

Hello, I try to start inference on my own images via command:
python3 inferencer.py --config=config/toponet_vitb_512_ekb.yaml --checkpoint=lightning_logs/vhfsw197/checkpoints/epoch=9-step=25000.ckpt

But then I got an error:

##### Loading Trained CKPT lightning_logs/vhfsw197/checkpoints/epoch=9-step=25000.ckpt #####
Traceback (most recent call last):
  File "/misc/home6/s0181/sam_road/inferencer.py", line 281, in <module>
    for img_id in test_img_indices:
NameError: name 'test_img_indices' is not defined

line 281:

for img_id in test_img_indices:
        print(f'Processing {img_id}')
        # [H, W, C] RGB
        img = read_rgb_img(rgb_pattern.format(img_id))
        start_seconds = time.time()

and e.t.c.

I think the erorr is sampling with the dataset name. But for cityscale and spacenet need gt graph, which I don't have for my images.

if config.DATASET == 'cityscale':
        _, _, test_img_indices = cityscale_data_partition()
        rgb_pattern = './cityscale/20cities/region_{}_sat.png'
        gt_graph_pattern = 'cityscale/20cities/region_{}_graph_gt.pickle'
    elif config.DATASET == 'spacenet':
        _, _, test_img_indices = spacenet_data_partition()
        rgb_pattern = './spacenet/RGB_1.0_meter/{}__rgb.png'
        gt_graph_pattern = './spacenet/RGB_1.0_meter/{}__gt_graph.p'

I used the configuration reference from your toponet_vitb_1024.yaml
toponet_vitb_512_ekb.yaml:

SAM_VERSION: 'vit_b'
SAM_CKPT_PATH: 'sam_ckpts/sam_vit_b_01ec64.pth'
PATCH_SIZE: 512
BATCH_SIZE: 16
DATA_WORKER_NUM: 1
TRAIN_EPOCHS: 10
BASE_LR: 0.001
FREEZE_ENCODER: False
ENCODER_LR_FACTOR: 0.1
ENCODER_LORA: False
FOCAL_LOSS: False
USE_SAM_DECODER: False

# TOPONET
# sample per patch
TOPO_SAMPLE_NUM: 256

# Inference
INFER_BATCH_SIZE: 64
SAMPLE_MARGIN: 64
INFER_PATCHES_PER_EDGE: 16

# [0, 255]
ITSC_THRESHOLD: 128
ROAD_THRESHOLD: 128
# pixels
ITSC_NMS_RADIUS: 8
ROAD_NMS_RADIUS: 16
NEIGHBOR_RADIUS: 64
MAX_NEIGHBOR_QUERIES: 16

Please, can you explane me what I need to do to solve the problem?