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README.md

@@ -1,12 +1,6 @@
 ---
-title: Image Captioning
-emoji: 🔥
-colorFrom: yellow
-colorTo: pink
+title: Image_Captioning
+app_file: app.py
 sdk: gradio
 sdk_version: 3.44.1
-app_file: app.py
-pinned: false
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,26 @@
+import torch
+from PIL import Image
+import gradio as gr
+
+from lavis.models import load_model_and_preprocess
+
+device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+model, vis_processors, _ = load_model_and_preprocess(
+    name="blip_caption", model_type="large_coco", is_eval=True, device=device
+)
+
+def predict(image):
+    pre_processed_image = vis_processors["eval"](image).unsqueeze(0).to(device)
+    response = model.generate({"image": pre_processed_image}, use_nucleus_sampling=True, num_captions=3)
+    return image, ",\n".join(response)
+
+demo = gr.Interface(
+    title="Image Captioning - BLIP",
+    fn=predict,
+    inputs=gr.Image(type='pil', label="Original Image"),
+    outputs=[gr.Image(type="pil"), gr.Textbox()],
+    examples=["example_1.jpg", "example_2.jpg"],
+)
+
+demo.launch()

requirements.txt

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+salesforce-lavis