Update README.md

README.md

@@ -1,8 +1,80 @@
 ---
-license: unlicense
+tags:
+- image-to-text
+- image-captioning
 language:
 - ru
 metrics:
-- rouge
-pipeline_tag: image-to-text
----
+- bleu
+library_name: transformers
+---
+
+# vit-rugpt2-image-captioning
+
+This is an image captioning model trained on translated version (en-ru) of dataset COCO2014.
+
+# Metrics on test data
+
+* Bleu: 8.672
+* Bleu precision 1: 30.567
+* Bleu precision 2: 7.895
+* Bleu precision 3: 3.261
+
+# Sample running code
+
+```python
+
+from transformers import VisionEncoderDecoderModel, ViTFeatureExtractor, AutoTokenizer
+import torch
+from PIL import Image
+
+model = VisionEncoderDecoderModel.from_pretrained("vit-rugpt2-image-captioning")
+feature_extractor = ViTFeatureExtractor.from_pretrained("vit-rugpt2-image-captioning")
+tokenizer = AutoTokenizer.from_pretrained("vit-rugpt2-image-captioning")
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+model.to(device)
+
+max_length = 16
+num_beams = 4
+gen_kwargs = {"max_length": max_length, "num_beams": num_beams}
+
+def predict_caption(image_paths):
+  images = []
+  for image_path in image_paths:
+    i_image = Image.open(image_path)
+    if i_image.mode != "RGB":
+      i_image = i_image.convert(mode="RGB")
+
+    images.append(i_image)
+
+  pixel_values = feature_extractor(images=images, return_tensors="pt").pixel_values
+  pixel_values = pixel_values.to(device)
+
+  output_ids = model.generate(pixel_values, **gen_kwargs)
+
+  preds = tokenizer.batch_decode(output_ids, skip_special_tokens=True)
+  preds = [pred.strip() for pred in preds]
+  return preds
+
+predict_caption(['train2014/COCO_train2014_000000295442.jpg']) # ['Самолет на взлетно-посадочной полосе аэропорта.']
+
+```
+
+# Sample running code using transformers pipeline
+
+```python
+
+from transformers import pipeline
+
+image_to_text = pipeline("image-to-text", model="vit-rugpt2-image-captioning")
+
+image_to_text("train2014/COCO_train2014_000000296754.jpg") # [{'generated_text': 'Человек идет по улице с зонтом.'}]
+
+```
+
+
+# Contact for any help
+* https://huggingface.co/tuman
+* https://github.com/tumanov-a
+* https://t.me/tumanov_av