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app.py

@@ -114,6 +114,7 @@ def process_image(img_path):
     # Remove non alphanumeric characters
     image_path = re.sub(r"\W+", "", img_path)
     image_path = str(datetime.now()) + ".png"
+    image_path = image_path.replace(" ", "_")
 
     # Join to directory path
     inf_image = os.path.join("inference", img_path)
@@ -157,7 +158,7 @@ def process_image(img_path):
 
     return np_image
 
-
+# Category to name mapping
 with open("cat_to_name.json", "r") as f:
     cat_to_name = json.load(f)
 
@@ -225,7 +226,7 @@ def predict(image_path, model=model, category_names=cat_to_name, topk=5):
 
         return fig
 
-
+# Gradio Interface
 gr.Interface(
     predict,
     inputs=gr.inputs.Image(label="Upload a flower image", type="filepath"),