mgbam commited on
Commit
4beb159
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1 Parent(s): aa563db

Update app.py

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Files changed (1) hide show
  1. app.py +14 -7
app.py CHANGED
@@ -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",
@@ -38,6 +42,9 @@ if torch.cuda.is_available():
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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"""
@@ -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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- def analyze_and_display(image, clinical_context, modality):
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- report = analyze_medical_case(image, clinical_context, modality)
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- return report
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-
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- analyze_btn.click(analyze_and_display, [image_input, clinical_input, modality_select], report_output)
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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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+
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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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+
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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)