Update app.py

app.py

@@ -11,6 +11,7 @@ import gradio as gr
 
 model = M2M100ForConditionalGeneration.from_pretrained("facebook/m2m100_418M")
 tokenizer = M2M100Tokenizer.from_pretrained("facebook/m2m100_418M")
+
 pipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
 images="dog.jpg"
 
@@ -20,16 +21,20 @@ def shot(image, labels_text):
     
     PIL_image = Image.fromarray(np.uint8(image)).convert('RGB')
     labels = labels_text.split(",")
-    res = pipe(images=PIL_image, 
-           candidate_labels=labels,
-           hypothesis_template= "This is a photo of a {}")
-    return {dic["label"]: dic["score"] for dic in res}
-        # Translate 
+    
+    # Translate 
     tokenizer.src_lang = "en"
     encodedText = tokenizer(labels_text, return_tensors="pt")
     generatedTokens = model.generate(**encodedText, forced_bos_token_id=tokenizer.get_lang_id("ru"))    
     return tokenizer.batch_decode(generatedTokens, skip_special_tokens=True)[0]
 
+
+    res = pipe(images=PIL_image, 
+           candidate_labels=labels,
+           hypothesis_template= "This is a photo of a {}")
+    return {dic["label"]: dic["score"] for dic in res}
+    
+    
     
 iface = gr.Interface(shot, 
                     ["image", "text"],