Update hmc_grad.py

hmc_grad.py

@@ -51,10 +51,7 @@ PREDICTION_TO_STRING = ["A", "B", "C", "D"]
 Prepare the Classifier Model.
 """
 
-# Download the model's state dictionary from repository
-# GITHUB_URL = "https://raw.githubusercontent.com/GabrielEdradan/HMC-Grad/main/image_classifier.pth"
-# MODEL_PATH = "/content/model.pth"
-# os.system(f"wget {GITHUB_URL} -O {MODEL_PATH}")
+# Load the model's state dictionary
 model_state_dict = torch.load("image_classifier.pth")
 
 # Define the model class
@@ -523,18 +520,9 @@ def grade_and_analyze(item_answers, img_cor_arr, img_scr_arr, itm_ana_arr, scr_a
   return corrected_image
 
 """## THE INTERFACE
-Use Gradio to create a user-friendly interface.
+Use Gradio to create a user-friendly interface. Set the interface function here, and app.py will import it and run Gradio.
 """
 
-# Download the sample images for the demo interface
-# SAMPLE_IMAGES_FOLDER_URL = "https://raw.githubusercontent.com/GabrielEdradan/HMC-Grad/main/sample_images/"
-# IMAGE_SAVE_PATH = "/content/"
-
-# NUM_OF_SAMPLES = 2
-# for i in range(1, NUM_OF_SAMPLES + 1):
-#   suffix = f"sample_{i}.jpg"
-#   os.system(f"wget {SAMPLE_IMAGES_FOLDER_URL}{suffix} -O {IMAGE_SAVE_PATH}{suffix}")
-
 # Define the interface function
 # Takes in two inputs: the correction key (string) and the answer sheet images (Array[Array[image paths]])
 def interface_function(correction_key_string, *images):