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app.py

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+import torch
+from PIL import Image
+from strhub.data.module import SceneTextDataModule
+from strhub.models.utils import load_from_checkpoint, parse_model_args
+import gradio as gr
+
+
+# # Load model and image transforms
+# parseq = torch.hub.load('baudm/parseq', 'trba', pretrained=True).eval()
+from strhub.models.crnn.system import CRNN as ModelClass
+parseq = ModelClass.load_from_checkpoint("sneed.ckpt").eval()
+
+img_transform = SceneTextDataModule.get_transform(parseq.hparams.img_size)
+
+def captcha_solver(img):
+  img = img.convert('RGB')
+  img = img_transform(img).unsqueeze(0)
+
+  logits = parseq(img)
+  logits.shape
+  
+  # # Greedy decoding
+  pred = logits.softmax(-1)
+  label, confidence = parseq.tokenizer.decode(pred)
+  return label[0]
+
+demo = gr.Interface(fn=captcha_solver, inputs=gr.inputs.Image(type="pil"), outputs=gr.outputs.Textbox())
+demo.launch()