Update app.py
Browse files
app.py
CHANGED
@@ -8,7 +8,6 @@ import os
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from huggingface_hub import login
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login(os.environ["HF_KEY"])
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# Load the model and tokenizer
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model = AutoModelForVision2Seq.from_pretrained("stabilityai/japanese-stable-vlm", trust_remote_code=True, device_map='auto')
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processor = AutoImageProcessor.from_pretrained("stabilityai/japanese-stable-vlm", device_map='auto')
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@@ -42,7 +41,6 @@ def build_prompt(task="caption", input=None, sep="\n\n### "):
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return p
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# Define the function to generate text from the image and prompt
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@spaces.GPU(duration=120)
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def generate_text(image, task, input_text=None):
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prompt = build_prompt(task=task, input=input_text)
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inputs = processor(images=image, return_tensors="pt")
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@@ -60,21 +58,21 @@ def generate_text(image, task, input_text=None):
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return generated_text
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# Define the Gradio interface
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with gr.Row():
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image_input = gr.Image(label="Upload an image")
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task_input = gr.Radio(choices=["caption", "tag", "vqa"], value="caption", label="Select a task")
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text_input = gr.Textbox(label="Enter text (for tag or vqa tasks)")
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submit_btn = gr.Button("Submit")
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inputs = [image_input, task_input, text_input]
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outputs = chatbot
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submit_btn.click(generate_text, inputs, outputs, api_name="generate_text")
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chatbot.change(lambda x: print(f"Chatbot changed: {x}"), chatbot, chatbot)
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chatbot.select(lambda x: print(f"Chatbot selected: {x.value}, {x.selected}"), None, chatbot)
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chatbot.like(lambda x: print(f"Liked/Disliked: {x.index}, {x.value}, {x.liked}"), None, chatbot)
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from huggingface_hub import login
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login(os.environ["HF_KEY"])
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device = "cuda" if torch.cuda.is_available() else "cpu"
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model = AutoModelForVision2Seq.from_pretrained("stabilityai/japanese-stable-vlm", trust_remote_code=True, device_map='auto')
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processor = AutoImageProcessor.from_pretrained("stabilityai/japanese-stable-vlm", device_map='auto')
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return p
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# Define the function to generate text from the image and prompt
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def generate_text(image, task, input_text=None):
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prompt = build_prompt(task=task, input=input_text)
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inputs = processor(images=image, return_tensors="pt")
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return generated_text
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# Define the Gradio interface
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image_input = gr.Image(label="Upload an image")
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task_input = gr.Radio(choices=["caption", "tag", "vqa"], value="caption", label="Select a task")
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text_input = gr.Textbox(label="Enter text (for tag or vqa tasks)")
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output = gr.Textbox(label="Generated text")
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interface = gr.Interface(
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fn=generate_text,
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inputs=[image_input, task_input, text_input],
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outputs=output,
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examples=[
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["examples/example_image.jpg", "caption", None],
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["examples/example_image.jpg", "tag", "河津桜、青空"],
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["examples/example_image.jpg", "vqa", "OCRはできますか?"],
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],
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)
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interface.launch()
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