nougat fix

playground/models/nougat.py

@@ -2,4 +2,4 @@
 
 nougat = Nougat()
 
-out = nougat("path/to/image.png")
+out = nougat("large.png")

swarms/models/nougat.py

@@ -18,7 +18,7 @@ class Nougat:
     """
     Nougat
 
-    ArgsS:
+    Args:
         model_name_or_path: str, default="facebook/nougat-base"
         min_length: int, default=1
         max_new_tokens: int, default=30
@@ -35,7 +35,7 @@ def __init__(
         self,
         model_name_or_path="facebook/nougat-base",
         min_length: int = 1,
-        max_new_tokens: int = 30,
+        max_new_tokens: int = 5000,
     ):
         self.model_name_or_path = model_name_or_path
         self.min_length = min_length
@@ -50,14 +50,17 @@ def __init__(
         self.device = "cuda" if torch.cuda.is_available() else "cpu"
         self.model.to(self.device)
 
-    def get_image(self, img_path: str):
+    def get_image(self, img: str):
         """Get an image from a path"""
-        image = Image.open(img_path)
-        return image
+        img = Image.open(img)
 
-    def __call__(self, img_path: str):
+        if img.mode == "L":
+            img = img.convert("RGB")
+        return img
+
+    def __call__(self, img: str):
         """Call the model with an image_path str as an input"""
-        image = Image.open(img_path)
+        image = Image.open(img)
         pixel_values = self.processor(image, return_tensors="pt").pixel_values
 
         # Generate transcriptions, here we only generate 30 tokens
@@ -78,6 +81,7 @@ def __call__(self, img_path: str):
         return out
 
     def clean_nougat_output(raw_output):
+        """Clean the output from nougat to be more readable"""
         # Define the pattern to extract the relevant data
         daily_balance_pattern = (
             r"\*\*(\d{2}/\d{2}/\d{4})\*\*\n\n\*\*([\d,]+\.\d{2})\*\*"