added /tmp/external_xrays_299x299x3 to have imgs int the same repo instead on dataset repo

app.py

@@ -61,6 +61,6 @@ if __name__ == "__main__":
     print("Python version used:", sys.version)
 
     if is_spaces:
-        demo.launch(debug=True,  allowed_paths=[str(IMG_DIR.parent)],)
+        demo.launch(debug=True,  allowed_paths=[str(IMG_DIR), str(Path(local_dataset_dir))],)
     else:
         demo.launch(share=True, debug=True, server_name="127.0.0.1", server_port=7860)

base.py

@@ -11,12 +11,16 @@ from defs import class_to_disease_map
 import pandas as pd
 from typing import Mapping
 from pathlib import Path
+import shutil
 
 # -------CONSTANTS-------#
 TARGET_SIZE = (256, 256)  # target size for masked images
 # Your dataset repo on HF
 DATASET_REPO = "valste/lung-disease-xrays"
 
+EXAMPLES_DIR = Path("/tmp/external_xrays_299x299x3")
+EXAMPLES_DIR.mkdir(parents=True, exist_ok=True)
+
 # Download (or reuse cache) in the Space
 local_dataset_dir = snapshot_download(repo_id=DATASET_REPO, repo_type="dataset", allow_patterns=["external_xrays_299x299/*"],)
 print("Local dataset dir:", local_dataset_dir)
@@ -94,23 +98,22 @@ else:
     capsnet_model_path = os.path.join(
         ".", "models", "capsnet-4class-lung-disease-classifier", "model.keras"
     )
-    #capsnet_knl5_path = Path(r"C:\Users\User\VS_CODE_WORKSPACES\DataScience\ds_aug24_lung_desease_classification\mlruns_capsnet\923962217935764323\af22305e09b44dd686b2405b0f6c01d5\artifacts\model\data\model.keras") #conv2d_1 krnl=5
     gan_model_path = os.path.join(".", "models", "lung-segmentation-gan", "model.keras")
-    data_dir = os.path.join(".", "data", "external_xrays_299x299")
-    dataset = load_dataset(
-        "imagefolder", data_dir=data_dir, split="train"  # path to your local folder
-    )
-    for ex in dataset:
-        if "image" in ex:
-            imgs.append(ex["image"])
-            path = getattr(ex["image"], "filename", None) # string
-            if path:
-                img_paths.append([path])
-                img_names.append(os.path.basename(path))
-            else:
-                raise DemoException("Missing path")
-        else:
-            raise DemoException("Dataset examples do not contain 'image' field.")  
+    # data_dir = os.path.join(".", "external_xrays_299x299x3")
+    # dataset = load_dataset(
+    #     "imagefolder", data_dir=data_dir, split="train"  # path to your local folder
+    # )
+    # for ex in dataset:
+    #     if "image" in ex:
+    #         imgs.append(ex["image"])
+    #         path = getattr(ex["image"], "filename", None) # string
+    #         if path:
+    #             img_paths.append([path])
+    #             img_names.append(os.path.basename(path))
+    #         else:
+    #             raise DemoException("Missing path")
+    #     else:
+    #         raise DemoException("Dataset examples do not contain 'image' field.")  
 
 
 #----Load models----#
@@ -123,8 +126,15 @@ model_capsnet = tf.keras.models.load_model(capsnet_model_path, custom_objects=ca
 # ------------------------------------------------------------
 
 # Build example lists once
-img_paths = sorted(str(p) for p in IMG_DIR.glob("*.png"))
-img_names = [os.path.basename(p) for p in img_paths]    
+# img_paths = sorted(str(p) for p in IMG_DIR.glob("*.png"))
+# img_names = [os.path.basename(p) for p in img_paths]    
+
+for p in sorted(IMG_DIR.glob("*.png"))[:20]:
+    dst = EXAMPLES_DIR / p.name
+    shutil.copyfile(p, dst)
+
+    img_paths.append([str(dst)])   # gr.Examples expects list-of-inputs
+    img_names.append(p.name)
 
 
 # ------------------------------------------------------------