Create app.py

app.py

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+import gradio as gr
+import os
+from huggingface_hub import from_pretrained_keras
+import tensorflow as tf
+
+model = from_pretrained_keras("rushic24/bit")
+allImages = []
+directory = 'images'
+CLASSES = ['daisy', 'dandelion', 'roses', 'sunflowers', 'tulips']
+# iterate over files in images directory
+for filename in os.listdir(directory):
+    f = os.path.join(directory, filename)
+    if os.path.isfile(f):
+      allImages.append(f)
+
+def flower_classifier(image):
+  image = tf.image.resize(image, (224, 224))
+  image = image / 255.0
+  image = tf.expand_dims(image, 0)
+  pred =  model(image)
+  labeldict = dict(zip([CLASSES[i] for i in range(len(pred))], pred))
+  return labeldict
+
+
+iface = gr.Interface(flower_classifier,
+                     title = "Award-Winning Deep Learning Project",
+                     examples = allImages,
+                     inputs = gr.inputs.Image(),
+                     outputs = gr.outputs.Label(num_top_classes=5),
+                     capture_session=True)
+iface.launch(debug=True)