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Update app.py
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app.py
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@@ -1,11 +1,15 @@
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import gradio as gr
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import torch
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import numpy as np
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from transformers import AutoModelForCausalLM
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from janus.models import VLChatProcessor
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from PIL import Image
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import spaces
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# Medical Imaging Analysis Configuration
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MEDICAL_CONFIG = {
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"echo_guidelines": "ASE 2023 Standards",
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vl_chat_processor = VLChatProcessor.from_pretrained(model_path)
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# Medical Image Processing Pipelines
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def preprocess_echo(image):
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"""Process echocardiography images"""
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@@ -147,11 +154,11 @@ with gr.Blocks(title="Cardiac & Histopathology AI", theme=gr.themes.Soft()) as d
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label="Example Medical Cases"
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)
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@demo.func
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demo.launch(share=True)
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import gradio as gr
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import torch
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import numpy as np
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from transformers import AutoModelForCausalLM, AutoTokenizer
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from janus.models import VLChatProcessor
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from PIL import Image
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import spaces
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# Suppress specific warnings
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import warnings
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warnings.filterwarnings("ignore", category=FutureWarning)
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# Medical Imaging Analysis Configuration
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MEDICAL_CONFIG = {
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"echo_guidelines": "ASE 2023 Standards",
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vl_chat_processor = VLChatProcessor.from_pretrained(model_path)
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# **Fix: Set legacy=False in tokenizer to use the new behavior**
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vl_chat_processor.tokenizer = AutoTokenizer.from_pretrained(model_path, legacy=False)
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# Medical Image Processing Pipelines
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def preprocess_echo(image):
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"""Process echocardiography images"""
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label="Example Medical Cases"
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)
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# **Fixed: Removed @demo.func and used .click() correctly**
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analyze_btn.click(
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analyze_medical_case,
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[image_input, clinical_input, modality_select],
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report_output
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)
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demo.launch(share=True)
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