Upload 4 files

.gitattributes

@@ -33,3 +33,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
 *tfevents* filter=lfs diff=lfs merge=lfs -text
+digit_detector.keras filter=lfs diff=lfs merge=lfs -text

app.py

@@ -0,0 +1,46 @@
+import gradio as gr
+import tensorflow as tf
+import numpy as np
+from PIL import Image
+
+model = tf.keras.models.load_model('digit_detector.keras')
+
+def predict_digit(image):
+    if image is None:
+        return {"error": "No image provided"}
+    
+    try:
+        if len(image.shape) == 3:
+            img = Image.fromarray(image.astype('uint8')).convert('L')
+        else:
+            img = Image.fromarray(image.astype('uint8'))
+        
+        img = img.resize((28, 28))
+        img_array = np.array(img)
+        img_array = 255 - img_array
+        img_array = img_array / 255.0
+        img_array = img_array.reshape(1, 28, 28, 1)
+        
+        prediction = model.predict(img_array, verbose=0)
+        digit = int(np.argmax(prediction))
+        confidence = float(np.max(prediction) * 100)
+        probabilities = [float(p) for p in prediction[0]]
+        
+        return {
+            "digit": digit,
+            "confidence": confidence,
+            "probabilities": probabilities
+        }
+        
+    except Exception as e:
+        return {"error": str(e)}
+
+iface = gr.Interface(
+    fn=predict_digit,
+    inputs=gr.Image(type="numpy", label="Upload digit image"),
+    outputs=gr.JSON(label="Prediction Result"),
+    title="Digit Detector API"
+)
+
+if __name__ == "__main__":
+    iface.launch(server_name="0.0.0.0", server_port=7860)

digit_detector.keras

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:424572ae2466f7243c158a9bab1390a957e3d5a89cba815791ae567a4c0cd986
+size 831288

dockerfile

@@ -0,0 +1,19 @@
+FROM python:3.11-slim
+
+# Hugging Face Spaces requires user ID 1000
+RUN useradd -m -u 1000 user
+USER user
+ENV PATH="/home/user/.local/bin:$PATH"
+
+WORKDIR /app
+
+# Copy requirements first (for better caching)
+COPY --chown=user requirements.txt .
+RUN pip install --no-cache-dir --upgrade pip && \
+    pip install --no-cache-dir -r requirements.txt
+
+# Copy the rest of the files
+COPY --chown=user . .
+
+# Run the app on port 7860
+CMD ["python", "app.py"]

requirements.txt

@@ -0,0 +1,5 @@
+tensorflow==2.15.0
+gradio==4.44.0
+numpy==1.24.3
+Pillow==10.1.0
+matplotlib==3.7.2