OLD_app_visual_transcript.py

# import streamlit as st
# import cv2
# import tempfile
# import os
# from visual_transcription.src.api_calls import analyze_image_Azure_Vision_Analysis, analyze_image_gpt4  # Your custom function to call the API
# from visual_transcription.utils.initialise_LLM_models import Azure_Vision_analyse_dict
# from visual_transcription.utils.utilities import get_frame_timestamp, image_to_base64, insert_VT_into_AT
# import json

# # -----------------------------------------------
# # Initialise some of the session_state values
# # -----------------------------------------------

# if "Azure Vision Add Captions" not in st.session_state:
#     st.session_state["Azure Vision Add Captions"] = Azure_Vision_analyse_dict #TODO: Make more efficient - only one if statement required

# if "gpt-4o" not in st.session_state:
#     with open(r"visual_transcription\utils\chat_GPT.json", "r") as json_file:
#         gpt4o_into = json.load(json_file)
#         st.session_state['gpt-4o'] = {"prompt": gpt4o_into["prompt"], "max_words": gpt4o_into["max_words"]}
#         st.session_state['gpt-4o']["prompt"] = st.session_state['gpt-4o']["prompt"].replace("%MAX_WORDS%", gpt4o_into["max_words"])

# if "saved_frames" not in st.session_state:
#     st.session_state.saved_frames = dict()
# if 'video' not in st.session_state:
#     st.session_state.video = None
# if 'frame_number' not in st.session_state:
#     st.session_state.frame_number = 0
# if 'total_frames' not in st.session_state:
#     st.session_state.total_frames = 0
# if 'uploaded' not in st.session_state:
#     st.session_state.uploaded = False
# if 'uploaded_transcript_objects' not in st.session_state:
#     st.session_state.uploaded_transcript_objects = dict()
# if "audio_transcript" not in st.session_state:
#     st.session_state.audio_transcript = []

# st.title('Video Transcription Service')

# if st.session_state.audio_transcript == []:
#     uploaded_json = st.file_uploader('Drag and drop an audio transcript file here', type=['json'])
#     if uploaded_json is not None:
#         st.session_state.audio_transcript = json.load(uploaded_json)

# # -----------------------------------------------
# # Model Selection
# # -----------------------------------------------
# model_options = ['Azure Vision Add Captions', 'gpt-4o', 'Model C']
# selected_model = st.selectbox('Select a model for visual transcription', model_options)
# st.session_state['selected_model'] = selected_model

# # -----------------------------------------------
# # Display informaiton that is relevant to the selected_model
# # -----------------------------------------------
# if st.session_state['selected_model'] == "Azure Vision Add Captions":
#     visual_features_model_options = ["TAGS", "OBJECTS", "CAPTION", "DENSE_CAPTIONS", "READ", "SMART_CROPS", "PEOPLE"]
#     visual_features = st.multiselect('Select the visual aspects that the model should transcribe', visual_features_model_options)
#     st.session_state['Azure Vision Add Captions']["visual_features"] = visual_features

# if st.session_state['selected_model'] == "gpt-4o":

#     filter_options = ["hate", "protected_material_code", "protected_material_text", "self_harm", "sexual", "violence"]
#     selected_filters = st.multiselect('Select filters', filter_options)
#     print("selected_filters = ", selected_filters)
#     st.session_state['gpt-4o']["selected_filters"] = selected_filters

#     if "hate" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = "safe"
#         # chosen_severity = st.selectbox('select the filter severity for hate', severity_options)
#         st.session_state["gpt-4o"]["hate"] = chosen_severity

#     if "protected_material_code" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = "safe"
#         # chosen_severity = st.selectbox('select the filter severity for protected_material_code', severity_options)
#         st.session_state["gpt-4o"]["protected_material_code"] = chosen_severity

#     if "protected_material_text" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = "safe"
#         # chosen_severity = st.selectbox('select the filter severity for protected_material_text', severity_options)
#         st.session_state["gpt-4o"]["protected_material_text"] = chosen_severity

#     if "self_harm" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = "safe"
#         # chosen_severity = st.selectbox('select the filter severity for self harm', severity_options)
#         st.session_state["gpt-4o"]["self_harm"] = chosen_severity

#     if "sexual" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = "safe"
#         # chosen_severity = st.selectbox('select the filter severity for sexsual', severity_options)
#         st.session_state["gpt-4o"]["sexual"] = chosen_severity

#     if "violence" in selected_filters:
#         severity_options = ["safe"]
#         chosen_severity = st.selectbox('select the filter severity for violence', severity_options)
#         st.session_state["gpt-4o"]["violence"] = chosen_severity

#     max_words = str(st.text_input(label="Please select the maximum number of words that the VT may be", value=st.session_state['gpt-4o']["max_words"]))

#     st.session_state['gpt-4o']["prompt"] = st.session_state['gpt-4o']["prompt"].replace(st.session_state['gpt-4o']["max_words"], max_words)
#     st.session_state['gpt-4o']["max_words"] = max_words

#     # prompt = st.session_state['gpt-4o']["prompt"].replace(r"{max_words}", st.session_state['gpt-4o']["max_words"])
#     prompt = st.session_state['gpt-4o']["prompt"]
#     st.session_state['gpt-4o']["prompt"] = st.text_area(label="prompt", value=prompt)


# # -----------------------------------------------
# # File Uploader: Drag and Drop a Video File
# # -----------------------------------------------
# if not st.session_state.uploaded:
#     uploaded_file = st.file_uploader('Drag and drop a video file here', type=['mp4', 'avi', 'mov'])
# else:
#     uploaded_file = None

# if uploaded_file is not None:
#     if not st.session_state.uploaded:
#         st.success('Video uploaded successfully! Processing transcription...')
#         # Save the uploaded video to a temporary file
#         with tempfile.NamedTemporaryFile(delete=False, suffix='.mp4') as temp_file:
#             temp_file.write(uploaded_file.read())
#             temp_file_path = temp_file.name

#         st.write(f'Temporary file path: {temp_file_path}')
#         if not os.path.exists(temp_file_path):
#             st.error('Temporary file was not created successfully.')
#         else:
#             st.session_state.video = cv2.VideoCapture(temp_file_path)
#             if st.session_state.video.isOpened():
#                 st.session_state.total_frames = int(st.session_state.video.get(cv2.CAP_PROP_FRAME_COUNT))
#                 st.session_state.uploaded = True
#             else:
#                 st.error('Could not open video file.')

# # -----------------------------------------------
# # Display Video Frames and Controls
# # -----------------------------------------------
# if st.session_state.uploaded:
#     # Use a slider to select the frame number
#     frame_number = st.slider('Select frame', 0, st.session_state.total_frames - 1, st.session_state.frame_number)
#     st.session_state.frame_number = frame_number
#     st.write(f"frame_number: {st.session_state.frame_number}")

#     stframe = st.empty()
#     st.session_state.video.set(cv2.CAP_PROP_POS_FRAMES, st.session_state.frame_number)
#     ret, frame = st.session_state.video.read()
#     if ret:
#         frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
#         stframe.image(frame_rgb, channels='RGB')
#     else:
#         st.error('Could not read the frame.')

# # Navigation and Save Frame buttons
# col1, col2, col3 = st.columns(3)
# with col1:
#     if st.button('Move Left'):
#         if st.session_state.frame_number > 0:
#             st.session_state.frame_number -= 1
# with col2:
#     if st.button('Save Frame Index'):
#         # Ensure we capture the correct frame
#         st.session_state.video.set(cv2.CAP_PROP_POS_FRAMES, st.session_state.frame_number)
#         ret, frame = st.session_state.video.read()
#         if ret:
#             frame_rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
#             st.session_state.saved_frames[st.session_state.frame_number] = {
#                 'frame': frame_rgb,
#                 'has_visual_transcripts': False,
#                 'getting_visual_transcripts': False,
#                 'visual_transcripts': None
#             }
#             st.write(f'Saved frame index: {st.session_state.frame_number}')
#         else:
#             st.error('Could not capture the frame to save.')
# with col3:
#     if st.button('Move Right'):
#         if st.session_state.frame_number < st.session_state.total_frames - 1:
#             st.session_state.frame_number += 1

# # -----------------------------------------------
# # Sidebar: Display Saved Frames as Clickable Cards (using st.button)
# # -----------------------------------------------
# with st.sidebar:
#     st.markdown("### Selected Frames")
#     for frame_index, frame_info in sorted(st.session_state.saved_frames.items()):
#         base64_img = image_to_base64(frame_info['frame'])
#         transcript_text = frame_info['visual_transcripts'] if frame_info['visual_transcripts'] else 'No transcript yet'
        
#         # Display the card using Markdown for styling
#         st.markdown(f"""
#             <div style="border: 1px solid #ccc; padding: 10px; margin-bottom: 10px;">
#                 <h4>Frame {frame_index}</h4>
#                 <img src="data:image/jpeg;base64,{base64_img}" style="width:100%;" />
#                 <p>{transcript_text}</p>
#             </div>
#         """, unsafe_allow_html=True)
        
#         # Create a button below each card
#         if not frame_info['has_visual_transcripts']:
#             if st.button(f"Transcribe frame {frame_index}", key=f"btn_{frame_index}"):

#                 if st.session_state['selected_model'] == "Azure Vision Add Captions":
#                     response = analyze_image_Azure_Vision_Analysis(frame_info['frame'], st.session_state[st.session_state['selected_model']]['client'], st.session_state['Azure Vision Add Captions']["visual_features"])
#                     message = response["message"]


#                 elif st.session_state['selected_model'] == "gpt-4o":
#                     response = analyze_image_gpt4(frame_info['frame'], st.session_state["gpt-4o"]["prompt"])
#                     choices = response["choices"]
#                     message = choices[0]["message"]["content"]

#                 # elif st.session_state['selected_model'] == "new model":
#                 #     response = MODEL_FUNCTION(INPUTS)
#                 #     choices = response["choices"]
#                 #     message = choices[0]["message"]["content"]

#                 else:
#                     raise ValueError("Invalid model selected")

#                 print("This is the session state: ", st.session_state['selected_model'])

#                 st.session_state.saved_frames[frame_index]['visual_transcripts'] = message
#                 st.session_state.saved_frames[frame_index]['has_visual_transcripts'] = True
#                 st.session_state.saved_frames[frame_index]['time_stamp'] = get_frame_timestamp(frame_index, st.session_state.video)
#                 st.success("Visual transcriptions updated for frame nr: " + str(frame_index) + ".")

#         # Button to add a frame to the transcript objects
#         elif st.button(f"Add frame {frame_index} to transcript", key=f"add_{frame_index}"):
#             st.session_state.uploaded_transcript_objects[frame_index] = st.session_state.saved_frames[frame_index]
#             del st.session_state.saved_frames[frame_index]
#             st.success("Frame " + str(frame_index) + " added to transcript objects.")

# # -----------------------------------------------
# # Sidebar: Display Uploaded Transcript Messages via a Select Slider
# # -----------------------------------------------
# with st.sidebar:
#     st.markdown("### Uploaded Transcript Messages")

#     st.session_state.audio_transcript

#     if st.session_state.uploaded_transcript_objects:
        
#         for frame_index, frame_info in sorted(st.session_state.uploaded_transcript_objects.items()):
#             st.write(frame_info['visual_transcripts'], frame_info['time_stamp'])
#             insert_VT_into_AT(frame_info)

#             # Use a select slider (which allows discrete options) to choose a frame from the uploaded transcripts
#             transcript_message = st.session_state.uploaded_transcript_objects[frame_index]['visual_transcripts']
#         st.write("Transcript message:", transcript_message)
#     else:
#         st.write("No uploaded transcript objects yet.")

# # -----------------------------------------------
# # Sidebar: Refresh Button
# # -----------------------------------------------
# # with st.sidebar:
# #     if st.button('Refresh'):
# #         st.success('Reloaded')

# # -----------------------------------------------
# # Add Some Spacing at the Bottom
# # -----------------------------------------------
# st.markdown("<div style='height: 200px;'></div>", unsafe_allow_html=True)

# # Optionally, you can release the video capture object on app exit
# # if st.session_state.video is not None:
# #     st.session_state.video.release()