Create app.py

app.py

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+from transformers import MobileNetV2FeatureExtractor, MobileNetV2ForImageClassification
+from PIL import Image
+
+# Replace with the path to the directory containing the model files
+model_folder = "/path/to/your/model_folder"
+
+# Load the feature extractor
+feature_extractor = MobileNetV2FeatureExtractor.from_pretrained(model_folder)
+
+# Load the model
+model = MobileNetV2ForImageClassification.from_pretrained(model_folder)
+
+# Load the image
+image = Image.open("/path/to/your/image.jpg")
+
+# Preprocess the image
+inputs = feature_extractor(images=image, return_tensors="pt")
+
+# Make predictions
+outputs = model(**inputs)
+logits = outputs.logits
+
+# Model predicts one of the 1000 ImageNet classes
+predicted_class_idx = logits.argmax(-1).item()
+print("Predicted class:", model.config.id2label[predicted_class_idx])