Create app.py

app.py

@@ -0,0 +1,33 @@
+import os
+import tensorflow as tf
+import numpy as np
+import pandas as pd
+import matplotlib.pyplot as plt
+from tensorflow import keras
+
+import requests
+import PIL
+import io
+import matplotlib.pyplot as plt
+
+def download_image(url):
+    resp = requests.get(url)
+    resp.raise_for_status()
+    return PIL.Image.open(io.BytesIO(resp.content))
+
+from keras_cv_attention_models import convnext
+
+mm = convnext.ConvNeXtBase()
+
+downloaded_image = download_image(
+    "https://www.popsci.com/uploads/2021/09/21/Tortoise-on-ground-surrounded-by-plants.jpg?auto=webp"
+    )
+
+downloaded_image_np = np.array(downloaded_image)
+
+img = downloaded_image_np
+imm = keras.applications.imagenet_utils.preprocess_input(img, mode='torch')
+image_input = tf.expand_dims(tf.image.resize(imm, mm.input_shape[1:3]), 0)
+
+pred = mm(image_input)
+pred_np = pred.numpy()