app.py

app.py

@@ -6,17 +6,29 @@ import os
 import tkinter as tk
 from PIL import Image
 import json
+from datasets import load_dataset
 
+directory_path = load_dataset("HuberDa/Labeltest")
+print("Spaltennamen:", directory_path['train'].column_names)
+print("Erstes Beispiel im Train-Split:", directory_path['train'][0])
+count = 0   
 
-def image_generator(directory_path):
-    for filename in os.listdir(directory_path):
-        if filename.endswith(".jpg") or filename.endswith(".png"):
-            image_path = os.path.join(directory_path, filename)
-            image = Image.open(image_path)
-            image_array = np.array(image)
-            yield filename,image_array
+def image_generator(hf_dataset, split="train"):
+    image_column = None
+    for col in hf_dataset[split].column_names:
+        if isinstance(hf_dataset[split][0][col], np.ndarray) or isinstance(hf_dataset[split][0][col], Image.Image):
+            image_column = col
+            break
+           
+    if image_column is None:
+        raise ValueError("Keine Bildspalte gefunden!")
 
-directory_path = "C:\Users\danie\Downloads"
+    # Schleife durch das Dataset und generiere Bild-Arrays
+    for example in hf_dataset[split]:
+        image = example[image_column]  # Greife auf das Bild zu
+        image_array = np.array(image)  # Konvertiere es in ein NumPy-Array
+        filename = example['id'] if 'id' in example else "unknown"
+        yield filename, image_array
 
 # Create the generator
 image_gen = image_generator(directory_path)
@@ -24,7 +36,7 @@ image_gen = image_generator(directory_path)
 def record_input(fname:str, label:str):
   if label != "Pass":
     output = {"fname": fname, "label": label}
-    with open("/content/output.txt", 'a') as f:
+    with open("output.txt", 'a') as f:
       json.dump(output, f)
       f.write("\n")
   fname, image = next(image_gen)