Update app.py

app.py

@@ -10,6 +10,7 @@ import torch
 import torch.nn.functional as F
 from open_clip import create_model, get_tokenizer
 from torchvision import transforms
+import translators as ts
 
 from templates import openai_imagenet_template
 
@@ -43,6 +44,40 @@ preprocess_img = transforms.Compose(
 
 ranks = ("Kingdom", "Phylum", "Class", "Order", "Family", "Genus", "Species")
 
+languages = ["English", "Spanish", "French", "German", "Chinese"]
+
+def translate(text, source_lang, target_lang):
+    return ts.google(text, from_language=source_lang, to_language=target_lang)
+
+def translate_output(output, target_lang):
+    if target_lang == "English":
+        return output
+    translated = {}
+    for k, v in output.items():
+        translated[translate(k, "English", target_lang)] = v
+    return translated
+# Rest of code
+
+with gr.Row():
+    language_select = gr.Radio(choices=languages, value="English")
+    
+open_domain_btn.click(
+    fn=lambda img, rank: translate_output(
+        open_domain_classification(img, rank), 
+        language_select.value
+    ),
+    inputs=[img_input, rank_dropdown], 
+    outputs=[open_domain_output]  
+)
+zero_shot_btn.click(
+    fn=lambda img, classes: translate_output(
+        zero_shot_classification(img, classes),
+        language_select.value
+    ),
+    inputs=[img_input, classes_txt],
+    outputs=zero_shot_output  
+)
+
 open_domain_examples = [
     ["examples/Ursus-arctos.jpeg", "Species"],
     ["examples/Phoca-vitulina.png", "Species"],