Duplicate from hari31416/digit_recognizer

Co-authored-by: Harikesh Kushwaha <hari31416@users.noreply.huggingface.co>

.gitattributes

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README.md

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+---
+title: Digit Recognizer
+emoji: 🐨
+colorFrom: purple
+colorTo: purple
+sdk: gradio
+sdk_version: 3.32.0
+app_file: app.py
+pinned: false
+license: mit
+duplicated_from: hari31416/digit_recognizer
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr
+import numpy as np
+import tensorflow as tf
+
+# Load the model
+model = tf.keras.models.load_model("mnist.h5")
+
+
+# Define a function to predict the digit
+def predict_digit(img):
+    # Resize the image to 28x28 pixels
+    img = img.reshape((1, 28, 28, 1))
+    # Normalize the image
+    if img.max() > 1:
+        img = img / 255.0
+    # Predict the class
+    res = model.predict([img])[0]
+    # create  result dictionary
+    return {str(i): float(res[i]) for i in range(10)}
+
+
+with gr.Blocks(
+    css="style.css",
+    theme=gr.themes.Default(primary_hue="blue", secondary_hue="cyan"),
+) as app:
+    # create a header and a para
+    with gr.Row():
+        gr.Markdown(
+            """# MNIST Digit Recognizer
+            This app recognizes handwritten digits. The app uses a sketchpad to get the input image.
+            
+            Model used is a two layered Convolution network, followed by a fully connected layer and a softmax layer.
+            """,
+        )
+    with gr.Row():
+        gr.Markdown("## Sketchpad")
+        gr.Markdown("## Prediction")
+    # create a row
+    with gr.Row():
+        # create a sketchpad
+        sketchpad = gr.Sketchpad(
+            shape=(28, 28),
+            brush_radius=2,
+            elem_id="sketchpad",
+            label="Draw a digit here",
+        )
+        blank_sketchpad = gr.Sketchpad(
+            invert_colors=True, brush_radius=2, visible=False
+        )
+        # create a label
+        label = gr.Label(
+            num_top_classes=3,
+            elem_id="label",
+            label="Prediction",
+        )
+
+    # create a button
+    button = gr.Button("Predict", elem_id="btn_pred")
+    # bind the button to predict the digit
+    button.click(
+        predict_digit,
+        inputs=sketchpad,
+        outputs=label,
+    )
+
+    # create a clear button for sketchpad
+    clear_button = gr.Button("Clear", elem_id="btn_clr")
+    clear_button.click(lambda a: None, inputs=blank_sketchpad, outputs=sketchpad)
+
+app.launch(share=False)

mnist.h5

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+version https://git-lfs.github.com/spec/v1
+oid sha256:06b1503d9e13866c2aa1123972a65fa0843141661e494f84bdf5782056fa1d16
+size 465008

requirements.txt

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+tensorflow-cpu
+gradio

style.css

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+#btn_pred {
+    margin-left: 37.5%;
+    width: 25%;
+}
+
+#btn_clr {
+    margin-left: 37.5%;
+    width: 25%;
+}