Delete handler.py

handler.py

@@ -1,40 +0,0 @@
-import torch
-import string
-from PIL import Image
-from torchvision import transforms
-import io
-
-class EndpointHandler():
-    def __init__(self, path=""):
-        # TorchScript model load ho raha hai
-        self.model = torch.jit.load(f"{path}/master_brain_2026_final.pt")
-        self.model.eval()
-        self.chars = string.ascii_uppercase + string.ascii_lowercase + string.digits + "@#$%&="
-        self.blank_index = len(self.chars)
-        self.preprocess = transforms.Compose([
-            transforms.Resize((35, 142)),
-            transforms.ToTensor(),
-            transforms.Normalize((0.5,), (0.5,))
-        ])
-
-    def __call__(self, data):
-        inputs = data.pop("inputs", data)
-        # Base64 ya raw bytes ko handle karne ke liye
-        if isinstance(inputs, str):
-            import base64
-            inputs = Image.open(io.BytesIO(base64.b64decode(inputs))).convert('RGB')
-        else:
-            inputs = Image.open(io.BytesIO(inputs)).convert('RGB')
-        
-        img_tensor = self.preprocess(inputs).unsqueeze(0)
-        with torch.no_grad():
-            logits = self.model(img_tensor)
-            max_indices = torch.argmax(logits, dim=2).squeeze()
-            res = []
-            prev = -1
-            for idx in max_indices:
-                val = idx.item()
-                if val != self.blank_index and val != prev:
-                    res.append(self.chars[val])
-                prev = val
-        return {"prediction": "".join(res).strip()}