Amruthaa commited on
Commit
d91e943
1 Parent(s): 44b7d5d

Adding image captioning

Browse files
Files changed (1) hide show
  1. app.py +18 -8
app.py CHANGED
@@ -1,35 +1,45 @@
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  from transformers import pipeline
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  import gradio as gr
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- # text summarizer
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  summarizer = pipeline("summarization", model = "facebook/bart-large-cnn")
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-
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  def get_summary(text):
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  output = summarizer(text)
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  return output[0]["summary_text"]
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- # named entity recognition
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  ner_model = pipeline("ner", model = "dslim/bert-large-NER")
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-
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  def get_ner(text):
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  output = ner_model(text)
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  return {"text":text, "entities":output}
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  demo = gr.Blocks()
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  with demo:
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  gr.Markdown("# Try out some cool tasks!")
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- with gr.Tab("Text Summarizer"):
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  sum_input = [gr.Textbox(label="Text to Summarize", placeholder="Enter text to summarize...", lines=4)]
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- sum_output = [gr.Textbox(label="Summarized Text")]
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  sum_btn = gr.Button("Summarize text")
 
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  sum_btn.click(get_summary, sum_input, sum_output)
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  with gr.Tab("Named Entity Recognition"):
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  ner_input = [gr.Textbox(label="Text to find Entities", placeholder = "Enter text...", lines = 4)]
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  # ner_output = gr.Textbox()
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  ner_output = [gr.HighlightedText(label="Text with entities")]
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- allow_flagging = "never"
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  ner_btn = gr.Button("Generate entities")
 
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  ner_btn.click(get_ner, ner_input, ner_output)
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-
 
 
 
 
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  demo.launch()
 
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  from transformers import pipeline
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  import gradio as gr
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+ # 1. text summarizer
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  summarizer = pipeline("summarization", model = "facebook/bart-large-cnn")
 
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  def get_summary(text):
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  output = summarizer(text)
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  return output[0]["summary_text"]
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+ # 2. named entity recognition
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  ner_model = pipeline("ner", model = "dslim/bert-large-NER")
 
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  def get_ner(text):
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  output = ner_model(text)
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  return {"text":text, "entities":output}
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+ # 3. Image Captioning
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+ caption_model = pipeline("image-to-text", model = "Salesforce/blip-image-captioning-base")
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+ # processor = AutoProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
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+ def get_caption(img):
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+ output = caption_model(img)
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+ return output[0]["generated_text"]
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+
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+
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  demo = gr.Blocks()
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  with demo:
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  gr.Markdown("# Try out some cool tasks!")
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+ with gr.Tab("Text Summarization"):
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  sum_input = [gr.Textbox(label="Text to Summarize", placeholder="Enter text to summarize...", lines=4)]
 
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  sum_btn = gr.Button("Summarize text")
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+ sum_output = [gr.Textbox(label="Summarized Text")]
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  sum_btn.click(get_summary, sum_input, sum_output)
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  with gr.Tab("Named Entity Recognition"):
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  ner_input = [gr.Textbox(label="Text to find Entities", placeholder = "Enter text...", lines = 4)]
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  # ner_output = gr.Textbox()
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  ner_output = [gr.HighlightedText(label="Text with entities")]
 
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  ner_btn = gr.Button("Generate entities")
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+ # allow_flagging = "never"
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  ner_btn.click(get_ner, ner_input, ner_output)
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+ with gr.Tab("Image Captioning"):
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+ cap_input = [gr.Image(label="Upload Image"), type="pil"]
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+ cap_btn = gr.Button("Generate Caption")
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+ cap_output = [gr.Textbox(label="Caption")]
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+ cap_btn.click(get_caption, cap_input, cap_output)
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  demo.launch()