Import Spacy for NER

app.py

@@ -7,6 +7,8 @@ sys.path.append("CLIP_explainability/Transformer-MM-Explainability/")
 import torch
 import CLIP.clip as clip
 
+import spacy
+
 
 from clip_grounding.utils.image import pad_to_square
 from clip_grounding.datasets.png import (
@@ -22,6 +24,8 @@ clip.clip._MODELS = {
 device = "cuda" if torch.cuda.is_available() else "cpu"
 model, preprocess = clip.load("ViT-B/32", device=device, jit=False)
 
+NER = spacy.load("en_core_web_sm")
+
 # Gradio Section:
 def run_demo(image, text):
     orig_image = pad_to_square(image)

requirements.txt

@@ -97,6 +97,7 @@ Shapely==1.8.2
 six==1.16.0
 sniffio==1.2.0
 soupsieve==2.3.2.post1
+spacy
 stack-data==0.3.0
 tangled-up-in-unicode==0.2.0
 termcolor==1.1.0