fix uploads

create_submission.py

@@ -8,7 +8,7 @@
 if kaggle:
     os.system('pip install /kaggle/input/segmentation-models/pretrainedmodels-0.7.4/ > /dev/null')
     os.system('pip install /kaggle/input/segmentation-models/segmentation_models.pytorch/ > /dev/null')
-    package_path = 'kaggle/input/sources' # add unet script dataset
+    package_path = '/kaggle/input/sources' # add unet script dataset
     import sys
     sys.path.append(package_path)
 from datasets.steel_dataset import TestDataset
@@ -82,9 +82,9 @@ def create_submission(n_splits, model_name, batch_size, num_workers, mean, std,
     n_splits = [1] # [0, 1, 2, 3, 4]
 
     if kaggle:
-        sample_submission_path = 'kaggel/input/severstal-steel-defect-detection/sample_submission.csv'
-        test_data_folder = "kaggle/input/severstal-steel-defect-detection/test_images"
-        model_path = 'kaggle/input/checkpoints'
+        sample_submission_path = '/kaggle/input/severstal-steel-defect-detection/sample_submission.csv'
+        test_data_folder = "/kaggle/input/severstal-steel-defect-detection/test_images"
+        model_path = '/kaggle/input/checkpoints'
     else:
         sample_submission_path = 'datasets/Steel_data/sample_submission.csv'
         test_data_folder = 'datasets/Steel_data/test_images'

datasets/steel_dataset.py

@@ -18,7 +18,6 @@
 from utils.data_augmentation import data_augmentation
 from utils.rle_parse import mask2rle, make_mask
 from utils.visualize import image_with_mask_torch
-import pickle
 warnings.filterwarnings("ignore")
 
 

uploads.sh

@@ -10,6 +10,7 @@ if [ ! -d "kaggle" ]; then
   mkdir -p kaggle/sources
   mkdir -p kaggle/sources/models
   mkdir -p kaggle/sources/datasets
+  mkdir -p kaggle/sources/utils
   mkdir -p kaggle/checkpoints
   mkdir -p kaggle/submission
   mkdir -p kaggle/segmentation_models
@@ -28,6 +29,9 @@ cp models/model.py kaggle/sources/models
 cp datasets/steel_dataset.py kaggle/sources/datasets
 cp solver.py kaggle/sources
 cp classify_segment.py kaggle/sources
+cp utils/data_augmentation.py kaggle/sources/utils
+cp utils/rle_parse.py kaggle/sources/utils
+cp utils/visualize.py kaggle/sources/utils
 
 # 复制权重文件
 cp checkpoints/$model_name/*_best.pth kaggle/checkpoints

utils/data_augmentation.py

@@ -1,11 +1,6 @@
-import numpy as np
 import cv2
-import random
-import glob
 from matplotlib import pyplot as plt
-from PIL import Image
 import pandas as pd
-from tqdm import tqdm
 import sys
 import os
 from copy import deepcopy

utils/rle_parse.py

@@ -1,5 +1,4 @@
 import numpy as np
-import pandas as pd
 
 
 # https://www.kaggle.com/paulorzp/rle-functions-run-lenght-encode-decode

utils/visualize.py

@@ -1,7 +1,5 @@
 # 可视化操作
-import cv2
 import torch
-from PIL import Image
 import numpy as np