Image files shifted to HF dataset

.gitignore

@@ -1,3 +1,5 @@
 # secret keys
 service_account.json 
-app.ipynb
+app.ipynb
+# Hugging Face token
+hf_token.txt

app.py

@@ -4,10 +4,26 @@ from PIL import Image, ImageOps
 import numpy as np
 import gradio as gr
 from gspread import service_account_from_dict
+from huggingface_hub import HfApi, hf_hub_download
 
 # -------- Configuration --------
-folder_ai    = "images/AI"
-folder_real  = "images/Real"
+HF_TOKEN = os.environ["HF_TOKEN"]
+api = HfApi(token=HF_TOKEN)
+REPO_ID = "HotshotGoku/Images_Test_AI_or_Real"
+
+# List files in the dataset 
+all_files = api.list_repo_files(
+    repo_id=REPO_ID,
+    repo_type="dataset"
+)
+
+# Get the AI vs Real folders
+ai_remote   = [f for f in all_files if f.startswith("AI/")]
+real_remote = [f for f in all_files if f.startswith("Real/")]
+
+ai_files   = [hf_hub_download(repo_id=REPO_ID, repo_type="dataset",filename=path, token=HF_TOKEN) for path in ai_remote]
+real_files = [hf_hub_download(repo_id=REPO_ID, repo_type="dataset",filename=path, token=HF_TOKEN) for path in real_remote]
+
 history_file = "history_state.json"
 # --------------------------------
 
@@ -45,11 +61,6 @@ def get_new_grid(state=None):
     """
 
     attempt_count = (state or {}).get("attempt_count", 0)
-
-
-      # 2) Sample & shuffle images as before
-    ai_files   = [os.path.join(folder_ai, f) for f in os.listdir(folder_ai)   if f.endswith(".png")]
-    real_files = [os.path.join(folder_real, f) for f in os.listdir(folder_real) if f.endswith(".png")]
     t          = random.randint(4, 12)
     sel_ai     = random.sample(ai_files, t)
     sel_real   = random.sample(real_files, 16 - t)