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README (1).md

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+---
+title: Sketchulator
+emoji: 🐨
+colorFrom: yellow
+colorTo: indigo
+sdk: gradio
+sdk_version: 4.38.1
+app_file: app.py
+pinned: false
+license: mit
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app (2).py

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+from keras.models import load_model
+model=load_model('num_detect (1).h5')
+import  numpy as np
+import cv2
+from keras.preprocessing import image
+import matplotlib.pyplot as plt
+def mnist_compatible(image_path, target_size=(28, 28)):
+
+    img = cv2.imread(image_path, cv2.IMREAD_GRAYSCALE)
+    plt.imshow(img)
+    plt.show()
+
+
+
+    img_resized = cv2.resize(img, target_size)
+
+
+    img_inverted = 255 - img_resized
+
+
+    img_normalized = img_inverted.astype('float32') / 255.0
+
+
+    img_array = image.img_to_array(img_normalized)
+
+    img_reshaped = img_array.reshape((*target_size, 1))
+
+    return img_reshaped
+
+def recognize_digit(dict):
+    path1 = dict['composite']
+    arr = mnist_compatible(path1)
+
+    arr = np.expand_dims(arr, axis=0)
+    prediction = np.argmax(model.predict(arr))
+    return prediction
+
+def calculator(image1, operation, image2):
+    # Recognize the drawn digits
+    num1 = recognize_digit(image1)
+    num2 = recognize_digit(image2)
+
+    # Perform the calculator operation
+    if operation == "add":
+        result = num1 + num2
+    elif operation == "subtract":
+        result = num1 - num2
+    elif operation == "multiply":
+        result = num1 * num2
+    elif operation == "divide":
+        result = num1 / num2
+
+    return result
+import gradio as gr
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column():
+            image1 = gr.Paint(label="Draw First Number", type="filepath", brush=gr.Brush(colors=["#32cc70"]), canvas_size=(301, 301))
+            operation = gr.Radio(["add", "subtract", "multiply", "divide"])
+            image2 = gr.Paint(label="Draw Second Number", type="filepath", brush=gr.Brush(colors=["#32cc70"]), canvas_size=(301, 301))
+            submit_btn = gr.Button(value="Calculate")
+        with gr.Column():
+            result = gr.Textbox(label="Result")
+
+    submit_btn.click(calculator, inputs=[image1, operation, image2], outputs=[result])
+demo.launch(share='True')

gitattributes

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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
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+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
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+*.wasm filter=lfs diff=lfs merge=lfs -text
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+*.zip filter=lfs diff=lfs merge=lfs -text
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+*tfevents* filter=lfs diff=lfs merge=lfs -text

num_detect%20%281%29.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:12e7eeaea412ad6820f6c228b2fe51de97568d3c21a8b7db362dc03c2712b48d
+size 1505832

requirements (1).txt

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+tensorflow
+numpy
+opencv-python
+matplotlib
+pillow
+gradio