Create app.py

app.py

@@ -0,0 +1,56 @@
+from transformers import MarianTokenizer, MarianMTModel
+from gtts import gTTS
+import gradio as gr
+import gradio as gr
+import torch 
+import torchvision
+import torchvision.transforms as transforms
+import requests
+from einops import rearrange
+from transformers import AutoFeatureExtractor, DeiTForImageClassificationWithTeacher
+import matplotlib
+
+
+
+def imgtrans(img):
+
+  feature_extractor = AutoFeatureExtractor.from_pretrained('facebook/deit-base-distilled-patch16-384')
+  model = DeiTForImageClassificationWithTeacher.from_pretrained('facebook/deit-base-distilled-patch16-384')
+  inputs = feature_extractor(images=img, return_tensors="pt")
+  outputs = model(**inputs)
+  logits = outputs.logits
+  # model predicts one of the 21,841 ImageNet-22k classes
+  predicted_class_idx = logits.argmax(-1).item()
+  english=model.config.id2label[predicted_class_idx]
+  english=english.replace("_", " ")
+  english=english.split(',',1)[0]
+ 
+    
+  src = "en"  # source language
+  trg = "tl"  # target language
+
+  model_name = f"Helsinki-NLP/opus-mt-{src}-{trg}"
+  model = MarianMTModel.from_pretrained(model_name)
+  tokenizer = MarianTokenizer.from_pretrained(model_name)
+
+  sample_text = english.lower()
+  batch = tokenizer([sample_text], return_tensors="pt")
+
+  generated_ids = model.generate(**batch)
+  fil=tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0];
+  tts=gTTS(text=fil,lang='tl')
+  tts.save('filtrans.wav')
+  fil_sound='filtrans.wav'
+  english=english.lower()
+  tts=gTTS(text=english,lang='en')
+  tts.save('engtrans.wav')
+  eng_sound='engtrans.wav'
+  return fil_sound,fil,eng_sound,english
+  
+interface=gr.Interface(fn=imgtrans,
+                       inputs=gr.inputs.Image(shape=(224,224),label='Insert Image'),
+                       outputs=[gr.outputs.Audio(label='Filipino Pronunciation'),gr.outputs.Textbox(label='Filipino Label'),
+                       gr.outputs.Audio(label='English Pronunciation'),gr.outputs.Textbox(label='English label')],
+                       examples = ['220px-Modern_British_LED_Traffic_Light.jpg','aki_dog.jpg','cat.jpg','dog.jpg','plasticbag.jpg',
+                       'telephone.jpg','vpavic_211006_4796_0061.jpg','watch.jpg','wonder_cat.jpg','hammer.jpg'])
+interface.launch()