Update renovation.py

renovation.py

@@ -1,11 +1,12 @@
 import os
 import glob
 import random
-import zipfile
 
 import datasets
 from datasets.tasks import ImageClassification
-
+from datasets import load_dataset
+import os
+from huggingface_hub import login
 _HOMEPAGE = "https://github.com/your-github/renovation"
 
 _CITATION = """\
@@ -25,17 +26,16 @@ Data was collected by the your research lab.
 """
 
 _URLS = {
-    "Not Applicable": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Not Applicable.zip",
+    "Not Applicable": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Not Applicable.zip",
     "Very Poor": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Very Poor.zip",
-    "Poor": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Poor.zip",
-    "Fair": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Fair.zip",
-    "Good": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Good.zip",
-    "Excellent": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Excellent.zip",
-    "Exceptional": "https://huggingface.co/datasets/rshrott/photos/resolve/main/Exceptional.zip"
+    "Poor": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Poor.zip",
+    "Fair": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Fair.zip",
+    "Good": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Good.zip",
+    "Excellent": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Excellent.zip",
+    "Exceptional": "https://huggingface.co/datasets/rshrott/renovation/resolve/main/Exceptional.zip"
 }
 
 _NAMES = ["Not Applicable", "Very Poor", "Poor", "Fair", "Good", "Excellent", "Exceptional"]
-
 class Renovations(datasets.GeneratorBasedBuilder):
     """Renovations house images dataset."""
 
@@ -56,52 +56,49 @@ class Renovations(datasets.GeneratorBasedBuilder):
         )
 
     def _split_generators(self, dl_manager):
-        data_dir = dl_manager.download_and_extract(_URLS)
+        data_files = dl_manager.download_and_extract(_URLS)
         return [
             datasets.SplitGenerator(
                 name=datasets.Split.TRAIN,
                 gen_kwargs={
-                    "data_dir": data_dir,
+                    "data_files": data_files,
                     "split": "train",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.VALIDATION,
                 gen_kwargs={
-                    "data_dir": data_dir,
+                    "data_files": data_files,
                     "split": "val",
                 },
             ),
             datasets.SplitGenerator(
                 name=datasets.Split.TEST,
                 gen_kwargs={
-                    "data_dir": data_dir,
+                    "data_files": data_files,
                     "split": "test",
                 },
             ),
         ]
 
-
-    def _generate_examples(self, data_dir, split):
+    def _generate_examples(self, data_files, split):
         all_files_and_labels = []
-        for label in _NAMES:
-            folder_path = os.path.join(data_dir, label)
-            files = glob.glob(os.path.join(folder_path, "*.jpeg"))
-            for file in files:
-                all_files_and_labels.append((file, label))
-    
+        for label, path in data_files.items():
+            files = glob.glob(path + '/*.jpeg', recursive=True)
+            all_files_and_labels.extend((file, label) for file in files)
+
         random.seed(43)  # ensure reproducibility
         random.shuffle(all_files_and_labels)
-    
+
         num_files = len(all_files_and_labels)
         train_data = all_files_and_labels[:int(num_files*0.9)]
         val_test_data = all_files_and_labels[int(num_files*0.9):]  # This will be used for both val and test
-    
+
         if split == "train":
             data_to_use = train_data
         else:  # "val" or "test" split
             data_to_use = val_test_data
-    
+
         for idx, (file, label) in enumerate(data_to_use):
             yield idx, {
                 "image_file_path": file,
@@ -110,4 +107,3 @@ class Renovations(datasets.GeneratorBasedBuilder):
             }
 
 
-