Update soybean_dataset.py

soybean_dataset.py

@@ -122,40 +122,33 @@ class SoybeanDataset(datasets.GeneratorBasedBuilder):
                 name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["valid"]}),
         ]
         
-    def background(f):
-        @wraps(f)
-        def wrapped(*args, **kwargs):
-            loop = asyncio.get_event_loop()
-            if loop.is_running():
-                # If the loop is already running, we can't use run_in_executor directly.
-                # You would need to ensure this is handled correctly depending on your application's architecture.
-                raise RuntimeError("Asyncio loop already running")
-            return loop.run_in_executor(None, f, *args, **kwargs)
-        return wrapped
-
-    @background
-    # Define the download function that returns the response object
-    def download(self,url):
-        r = requests.get(url)
-        r.raise_for_status()  # This will raise an exception if there is a download error
-        return r
-    
-    # Define the process_image function that uses the response from download
-    def process_image(self, image_url):
-        response = self.download(image_url)
-        img = Image.open(BytesIO(response.content))
-        return img
+    def process_image(self,image_url):
+            response = requests.get(image_url)
+            response.raise_for_status()  # This will raise an exception if there is a download error
 
+            # Open the image from the downloaded bytes and return the PIL Image
+            img = Image.open(BytesIO(response.content))
+            return img
         
-
-
     def _generate_examples(self, filepath):
     #"""Yields examples as (key, example) tuples."""
         logging.info("generating examples from = %s", filepath)
-
+        with ThreadPoolExecutor(max_workers=5) as executor:
+            # Create a future to image mapping
+            future_to_image = {executor.submit(self.process_image, row['original_image']): row for row in data}
+
+            for future in as_completed(future_to_image):
+                row = future_to_image[future]
+                try:
+                    original_image = future.result()  # This will block until the image is ready
+                    # ... do something with the original_image ...
+                except Exception as e:
+                    logging.error(f"Error processing image: {e}")
+                    continue
+                    
         with open(filepath, encoding="utf-8") as f:
             data = csv.DictReader(f)
-
+            
 
             for row in data:
                 # Assuming the 'original_image' column has the full path to the image file
@@ -178,6 +171,7 @@ class SoybeanDataset(datasets.GeneratorBasedBuilder):
                     # ... add other features if necessary
                 }
     
+