Update app.py

app.py

@@ -4,12 +4,23 @@ from tensorflow.keras.preprocessing import image
 import numpy as np
 from PIL import Image
 from keras import layers
+from transformers import TFAutoModelForImageClassification
+from transformers import AutoImageProcessor
+
+# Load model#'model = tf.keras.models.load_model("xception-head")
+
+# Replace with your Hugging Face model repository name
+model_name = "icputrd/Inception-V3-Human-Bodypart-Classifier"
+
+# Load the pre-trained TensorFlow model from Hugging Face
+model = TFAutoModelForImageClassification.from_pretrained(model_name)
+
+# Load the associated image processor (for preprocessing input images)
+image_processor = AutoImageProcessor.from_pretrained(model_name)
 
-# Load your trained Xception model
-model = tf.keras.models.load_model("xception-head")
 
 # Define the labels for your classification
-class_labels = ['fresh', 'early decay', 'advanced decay','skeletonized']  # Replace with your actual class names
+class_labels = ['arm', 'hand', 'foot',  'legs','fullbody','head','backside', 'torso', 'stake', 'plastic'] # Replace with your actual class names
 
 def classify_image(img):
     # Preprocess the image to fit the model input shape
@@ -31,12 +42,11 @@ def classify_image(img):
 # Gradio interface
 demo = gr.Interface(
     fn=classify_image,
-    title="Human Decomposition Image Classification",
-    description = "Predict the stage of decay (fresh, early decay, advanced decay, or skeletonized) of a head. This is a demo of one of our human decomposition image classification <a href=\"https://huggingface.co/icputrd/megyesi_decomposition_classification/blob/main/head/xception\">models</a>.",
+    title="Human Bodypart Image Classification",
+    description = "Predict the bodypart of huma. This is a demo of our human bodypart image <a href=\"https://huggingface.co/icputrd/Inception-V3-Human-Bodypart-Classifier">classifier</a>.",
     inputs=gr.Image(type="pil"),
     outputs=[gr.Label(num_top_classes=len(class_labels)), gr.Number()],
     live=True,
-    article = "Author: <a href=\"https://www.linkedin.com/in/anna-maria-nau/\">Anna-Maria Nau</a>"
 )
 
 if __name__ == "__main__":