Add application file

app.py

@@ -0,0 +1,39 @@
+import gradio as gr
+from PIL import Image, ImageDraw
+import numpy as np
+import cv2
+import tensorflow as tf
+
+nn = tf.keras.models.load_model('nn.keras')
+
+def detect_object(img):
+  draw = ImageDraw.Draw(img)
+
+  img_array = img.convert("L")
+  img_array = np.array(img_array)
+  orig_h, orig_w = img_array.shape
+  
+  img_re = cv2.resize(img_array, (64, 64))
+  img_norm = img_re.astype('float32') / 255.0
+
+  result = nn.predict(img_norm.reshape(1, -1))
+  result *= [orig_w, orig_h, orig_w, orig_h]
+  
+  xmin, ymin, xmax, ymax = result[0]
+  xmax += xmin
+  ymax += ymin
+
+  draw.rectangle([xmin, ymin, xmax, ymax], outline="red", width=2)
+
+  return img
+
+interface = gr.Interface(
+    fn=detect_object,
+    inputs=gr.Image(type="pil", label="Upload an Image"),
+    outputs=gr.Image(type="pil", label="Detected object"),
+    title="Object Detection",
+    description="Simple Neural Network Model For Object Detection"
+)
+
+if __name__ == "__main__":
+  interface.launch(share=True)