Moved test2.py to app-old. This implementation pulls model and stuff from hugging faces.

models/app-old.py

@@ -0,0 +1,39 @@
+# Import libraries
+from PIL import Image, UnidentifiedImageError
+from transformers import ViTImageProcessor, ViTForImageClassification
+
+# Load the image processor and model
+model_name = 'vishnun0027/Crop_Disease_model_1'
+image_processor = ViTImageProcessor.from_pretrained(model_name)
+model = ViTForImageClassification.from_pretrained(
+    model_name,
+    ignore_mismatched_sizes=True
+)
+
+# Load image
+try:
+    image = Image.open('/home/overnion/Status200/tomato.png')
+    # Convert the image to RGB if it's not already
+    if (image.mode != 'RGB'):
+        image = image.convert('RGB')
+except FileNotFoundError:
+    print("Error: Image file not found.")
+    exit()
+except UnidentifiedImageError:
+    print("Error: Unable to open image. Check the file type.")
+    exit()
+except Exception as e:
+    print(f"An error occurred: {e}")
+    exit()
+
+# Preparing the image for the model
+inputs = image_processor(images=image, return_tensors="pt")
+
+# Make the prediction
+outputs = model(**inputs)
+logits = outputs.logits
+predicted_class_idx = logits.argmax(-1).item()
+
+# Print the predicted class
+print("Predicted class:", model.config.id2label[predicted_class_idx])
+