mabu-dev
commented
2 years ago Hi @kavi0786, I managed to isolate what's causing this issue and it turns out to be a series of problems.
Issue 1: Data First of all, there are 2 things wrong with the dataset.
- There's an incorrect image path: "imagePath": "..\butterfly (1).png".
- There's a further erroneous image path in some examples:
The code below will resolve these data issues:
import json
import os
from tqdm import tqdm
DATA_DIR = "Datasets/Nature"
for _dir in os.listdir(f"{DATA_DIR}"):
DATA_SET = f"{DATA_DIR}/{_dir}"
for file in tqdm(os.listdir(DATA_SET)):
if file.endswith(".json"):
with open(os.path.join(DATA_SET, file), 'r') as f:
data = json.load(f)
data['imagePath'] = data['imagePath'].replace(
'..\\', '').replace("images\\", "")
with open(os.path.join(DATA_SET, file), 'w') as f:
json.dump(data, f)Issue 2: Compatibility with labelme2coco.convert()
However, solving these data issues actually raises new problems. convert actually expects an export directory as shown below, but a file name is being passed. It also handles the naming of export files differently, depending on train_split_rate:
See the below for the before and after of how to fix load_dataset. This fix is probably hacky because it still doesn't support custom train with valid set, we probably wanna fix this.
*Issue 3: labelme2coco.convert() does not respect the 0 class ID reservation
This means we'll always throw the below error:
A quick fix is a bit hacky, but it works logically!
class_id = category['id'] + 1 will ensure class IDs are > 0.
SUCCESS! I got it working by following the above step. I'll create a PR and you can checkout to branch and use this fix while the PR is in review and hopefully gets some improvements.
chukwujike
kurattila
hobbitsyfeet
Madam, while i am executing the custom instance segmentation- MaskRCNN in googlecolab, i am getting the error. please see and let me know where i can modify....i am waiting for your reply..thanks in advance.
Kavitha