mirror of
https://github.com/oobabooga/text-generation-webui.git
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56 lines
2.4 KiB
Python
56 lines
2.4 KiB
Python
import base64
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from io import BytesIO
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import gradio as gr
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import modules.chat as chat
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import modules.shared as shared
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import torch
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from PIL import Image
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from transformers import BlipForConditionalGeneration, BlipProcessor
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# If 'state' is True, will hijack the next chat generation with
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# custom input text given by 'value' in the format [text, visible_text]
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input_hijack = {
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'state': False,
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'value': ["", ""]
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}
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processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base", torch_dtype=torch.float32).to("cpu")
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def caption_image(raw_image):
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inputs = processor(raw_image.convert('RGB'), return_tensors="pt").to("cpu", torch.float32)
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out = model.generate(**inputs, max_new_tokens=100)
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return processor.decode(out[0], skip_special_tokens=True)
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def generate_chat_picture(picture, name1, name2):
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text = f'*{name1} sends {name2} a picture that contains the following: "{caption_image(picture)}"*'
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# lower the resolution of sent images for the chat, otherwise the log size gets out of control quickly with all the base64 values in visible history
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width, height = picture.size
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if (width > 300):
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height = int(height * (300 / width))
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width = 300
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elif (height > 300):
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width = int(width * (300 / height))
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height = 300
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newsize = (width, height)
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picture = picture.resize(newsize, Image.LANCZOS)
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buffer = BytesIO()
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picture.save(buffer, format="JPEG")
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img_str = base64.b64encode(buffer.getvalue()).decode('utf-8')
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visible_text = f'<img src="data:image/jpeg;base64,{img_str}" alt="{text}">'
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return text, visible_text
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def ui():
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picture_select = gr.Image(label='Send a picture', type='pil')
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function_call = 'chat.cai_chatbot_wrapper' if shared.args.cai_chat else 'chat.chatbot_wrapper'
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# Prepare the hijack with custom inputs
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picture_select.upload(lambda picture, name1, name2: input_hijack.update({"state": True, "value": generate_chat_picture(picture, name1, name2)}), [picture_select, shared.gradio['name1'], shared.gradio['name2']], None)
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# Call the generation function
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picture_select.upload(eval(function_call), shared.input_params, shared.gradio['display'], show_progress=shared.args.no_stream)
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# Clear the picture from the upload field
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picture_select.upload(lambda : None, [], [picture_select], show_progress=False) |