Spaces:
Running
Running
phyloforfun
commited on
Commit
•
dc252b5
1
Parent(s):
0ee709f
file upload gallery
Browse files
app.py
CHANGED
@@ -1219,29 +1219,16 @@ def show_header_welcome():
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st.image(st.session_state.logo, width=250)
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def content_header():
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col_run_1, col_run_2, col_run_3 = st.columns([
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col_test = st.container()
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st.write("")
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st.write("")
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st.write("")
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st.write("")
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st.subheader("Overall Progress")
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col_run_info_1 = st.columns([1])[0]
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st.write("")
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st.write("")
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st.write("")
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st.header("Configuration Settings")
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with col_run_info_1:
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# Progress
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# Progress
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# st.subheader('Project')
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# bar = st.progress(0)
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# new_text = st.empty() # Placeholder for current step name
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# progress_report = ProgressReportVV(bar, new_text, n_images=10)
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# Progress
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overall_progress_bar = st.progress(0)
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text_overall = st.empty() # Placeholder for current step name
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@@ -1303,11 +1290,12 @@ def content_header():
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st.write('3. Choose a LLM version --- Only LLMs with valid keys will appear in the dropdown list.')
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st.write('4. Select a prompt version --- Start with "Version 2". Custom Prompts will include ".yaml" in the name. You can build your own Custom Prompt in the Prompt Builder.')
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st.markdown('5. Upload images --- Up to ~100 images can be uploaded in the Hugging Face Spaces implementation. If you want to process more images at once (and have more control in general) then use the [GitHub version](https://github.com/Gene-Weaver/VoucherVision). If you pay for persistent storage for your HF Space, then you may be able to process more too.')
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st.write('6. LeafMachine2 collage --- If selected, LeafMachine2 will isolate all text from the image and create a label collage, which will be sent to the OCR algorithm instead of the full image. This improves OCR detection for small or finely written text.')
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st.write('7. OCR overlay images --- If selected, VoucherVision will overlay the OCR detections onto the input image. This is useful for debugging transcription errors to see if the OCR failed or if the LLM failed.')
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st.write('8. Start processing --- Wait for VoucherVision to finish.')
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st.write('9. Download results --- Click the "Download Results" button to save the VoucherVision output to your computer. ***Output files will disappear if you start a new run or restart the Space.***')
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st.write('
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# st.subheader('Run Tests', help="")
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# st.write('We include a single image for testing. If you want to test all of the available prompts and LLMs on a different set of images, copy your images into `../VoucherVision/demo/demo_images`.')
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# if st.button("Test GPT",disabled=True):
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@@ -1324,7 +1312,7 @@ def content_header():
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# display_test_results(test_results, JSON_results, 'palm')
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# st.balloons()
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with
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st.subheader('Available LLMs and APIs')
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show_available_APIs()
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st.info('Until the end of 2023, Azure OpenAI models will be available for anyone to use here. Then only PaLM 2 will be available. To use all services, duplicate this Space and provide your own API keys.')
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st.image(st.session_state.logo, width=250)
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def content_header():
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col_run_1, col_run_2, col_run_3, col_run_4 = st.columns([2,2,2,2])
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st.write("")
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st.subheader("Overall Progress")
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col_run_info_1 = st.columns([1])[0]
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st.write("")
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st.header("Configuration Settings")
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with col_run_info_1:
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# Progress
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overall_progress_bar = st.progress(0)
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text_overall = st.empty() # Placeholder for current step name
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st.write('3. Choose a LLM version --- Only LLMs with valid keys will appear in the dropdown list.')
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st.write('4. Select a prompt version --- Start with "Version 2". Custom Prompts will include ".yaml" in the name. You can build your own Custom Prompt in the Prompt Builder.')
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st.markdown('5. Upload images --- Up to ~100 images can be uploaded in the Hugging Face Spaces implementation. If you want to process more images at once (and have more control in general) then use the [GitHub version](https://github.com/Gene-Weaver/VoucherVision). If you pay for persistent storage for your HF Space, then you may be able to process more too.')
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with col_run_3:
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st.write('6. LeafMachine2 collage --- If selected, LeafMachine2 will isolate all text from the image and create a label collage, which will be sent to the OCR algorithm instead of the full image. This improves OCR detection for small or finely written text.')
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st.write('7. OCR overlay images --- If selected, VoucherVision will overlay the OCR detections onto the input image. This is useful for debugging transcription errors to see if the OCR failed or if the LLM failed.')
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st.write('8. Start processing --- Wait for VoucherVision to finish.')
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st.write('9. Download results --- Click the "Download Results" button to save the VoucherVision output to your computer. ***Output files will disappear if you start a new run or restart the Space.***')
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st.write('10. Editing the LLM transcriptions --- Use the VoucherVisionEditor to revise and correct any mistakes or ommissions.')
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# st.subheader('Run Tests', help="")
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# st.write('We include a single image for testing. If you want to test all of the available prompts and LLMs on a different set of images, copy your images into `../VoucherVision/demo/demo_images`.')
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# if st.button("Test GPT",disabled=True):
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# display_test_results(test_results, JSON_results, 'palm')
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# st.balloons()
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with col_run_4:
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st.subheader('Available LLMs and APIs')
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show_available_APIs()
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st.info('Until the end of 2023, Azure OpenAI models will be available for anyone to use here. Then only PaLM 2 will be available. To use all services, duplicate this Space and provide your own API keys.')
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