Duplicate from Hentinel/pixelplanet_captcha

.gitattributes

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README.md

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+---
+title: Pixelplanet Captcha
+emoji: 🏃
+colorFrom: blue
+colorTo: pink
+sdk: gradio
+sdk_version: 3.36.1
+app_file: app.py
+pinned: false
+duplicated_from: Hentinel/pixelplanet_captcha
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import onnxruntime as onr
+import numpy as np
+import gradio as gr
+import glob
+#----- CONFIG ------
+img_height = 300
+img_width = 500
+max_length = 4
+characters = ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9', 'A', 'B', 'C', 'D', 'E', 
+              'F', 'G', 'H', 'I', 'J', 'K', 'L', 'M', 'N', 'O', 'P', 'Q', 'R', 'S', 'T', 
+              'U', 'V', 'W', 'X', 'Y', 'Z', 'a', 'b', 'c', 'd', 'e', 'f', 'g', 'h', 'i', 
+              'j', 'k', 'l', 'm', 'n', 'o', 'p', 'q', 'r', 's', 't', 'u', 'v', 'w', 'x', 
+              'y', 'z'
+              ]
+model_path = 'model.onnx'
+#===== some code init =====
+Model = onr.InferenceSession(model_path)
+
+#===== some funcs =====
+def get_result(pred):
+        accuracy = 1
+        last = None
+        ans = []
+        for item in pred[0]:
+            char_ind = item.argmax()
+            if char_ind != last and char_ind != 0 and char_ind != len(characters) + 1:
+                ans.append(characters[char_ind - 1])
+                accuracy *= item[char_ind]
+            last = char_ind
+        answ = "".join(ans)[:max_length]
+        return answ, accuracy
+def predict(img):
+    img = img.convert('L')
+    img = img.resize((img_width, img_height))
+    img = np.array(img)
+    img = np.expand_dims(img, axis=1)
+    img = np.expand_dims(img, axis=-1)
+    img = img.transpose([1,2,0,3])
+    img = img.astype(np.float32) / 255.
+    result_tensor = Model.run(None, {'image': img, 'label': np.random.default_rng().random((28, 28), dtype=np.float32)})[0]
+    return (get_result(result_tensor)[0])
+
+title = "Made with love❤️❤️❤️❤️\nby Vermei"
+description = "read meinkampf first"
+
+iface = gr.Interface(fn=predict, 
+                     inputs=gr.inputs.Image(type='pil'), 
+                     outputs=gr.outputs.Textbox(),
+                     title=title,
+                     examples=glob.glob('examples/*.png'),
+                     description=description)
+iface.launch()

model.onnx

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+oid sha256:26cec4eda2fc18613b458b3f4d022a24a27897af21938ef340dd279cc0565390
+size 2808688

requirements.txt

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+onnx==1.14.0
+onnxruntime==1.15.1

vermei_slaves.h5

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