feat: Update backend to use custom-trained model

generate_config.py

@@ -0,0 +1,20 @@
+from transformers import AutoImageProcessor
+
+# The model you used as a base for fine-tuning
+BASE_MODEL = "Mullerjo/food-101-finetuned-model"
+
+# A local directory where the config file will be saved
+SAVE_DIRECTORY = "my-indian-food-model-processor"
+
+print(f"Loading the image processor from '{BASE_MODEL}'...")
+
+# Load the processor associated with the base model
+processor = AutoImageProcessor.from_pretrained(BASE_MODEL)
+
+print(f"Saving the processor's configuration to the '{SAVE_DIRECTORY}' folder...")
+
+# This creates the 'preprocessor_config.json' file inside the save directory
+processor.save_pretrained(SAVE_DIRECTORY)
+
+print("\nSuccess!")
+print(f"The 'preprocessor_config.json' file has been created in the '{SAVE_DIRECTORY}' folder.")

my-indian-food-model-processor/preprocessor_config.json

@@ -0,0 +1,23 @@
+{
+  "do_convert_rgb": null,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}