Update ct_seg_gradio.py

ct_seg_gradio.py

@@ -4,8 +4,11 @@ import time
 import os
 from glob import glob
 from PIL import Image
+from huggingface_hub import HfApi
 #import torchvision.transforms as transforms
 
+api = HfApi()
+
 num_rank = 200
 image_prefix = "ct_synthetic_60_large/"
 mask_prefix = "ct/orig_masks/"
@@ -59,6 +62,10 @@ def find_completed_idxs(save_path=save_path):
         return file_list, incorrect_files
 
 def load_next(rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4, example, ids=image_ids, image_prefix=image_prefix, save_path=save_path):
+    api.upload_folder(
+    folder_path="/home/user/app/ct_seg_ranks",
+    repo_id="eprakash/gradio",
+    repo_type="space",)
     file_list, incorrect_files = find_completed_idxs()
     print(str(file_list) + " " + str(incorrect_files))
     if (int(example) not in file_list or int(example) in incorrect_files):
@@ -66,6 +73,10 @@ def load_next(rank, img_1, mask_1, img_2, mask_2, img_3, mask_3, img_4, mask_4,
         r_fp = open(save_path + "/" + str(int(example)) +".txt", "w")
         r_fp.write(r + "\n")
         r_fp.close()
+    api.upload_folder(
+    folder_path="/home/user/app/ct_seg_ranks",
+    repo_id="eprakash/gradio",
+    repo_type="space",)
     file_list, incorrect_files = find_completed_idxs()
     if (len(incorrect_files) != 0):
         example = incorrect_files[-1]