diff --git a/edge_streamlit/Dockerfile b/edge_streamlit/Dockerfile
index bcca18a7..4397d86a 100644
--- a/edge_streamlit/Dockerfile
+++ b/edge_streamlit/Dockerfile
@@ -27,4 +27,4 @@ EXPOSE 8501
HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
-ENTRYPOINT ["streamlit", "run", "app-basic.py"]
+ENTRYPOINT ["streamlit", "run", "app.py"]
diff --git a/edge_streamlit/Makefile b/edge_streamlit/Makefile
index a12a93c7..0c03e73f 100644
--- a/edge_streamlit/Makefile
+++ b/edge_streamlit/Makefile
@@ -18,7 +18,7 @@ env:
.PHONY: run ## Run the streamlit app
run:
- streamlit run app-basic.py
+ streamlit run app.py
.PHONY: linting ## 🐍 Lint Python files to conform to the PEP 8 style guide
linting:
diff --git a/edge_streamlit/app-basic.py b/edge_streamlit/app-basic.py
deleted file mode 100644
index 5b3656a6..00000000
--- a/edge_streamlit/app-basic.py
+++ /dev/null
@@ -1,106 +0,0 @@
-import json
-import os
-import time
-import requests
-import streamlit as st
-from prediction_boxes import filtering_items_that_have_predictions, plot_predictions
-from PIL import Image
-from io import BytesIO
-
-# Page configuration
-st.set_page_config(page_title="VIO-edge", page_icon="🔦", layout="wide")
-
-URL_ORCH = os.getenv("ORCHESTRATOR_URL", "http://localhost:8000/api/v1/")
-
-url_config = URL_ORCH + "configs"
-url_active_config = URL_ORCH + "configs/active"
-url_trigger = URL_ORCH + "trigger"
-
-
-def main():
- """
- Fonction principale de l'application Streamlit.
- """
- # Init variables
- active_config = json.loads(requests.get(url_active_config).text)
- if active_config:
- st.session_state.active_config = active_config
-
- if "active_config" not in st.session_state:
- st.session_state.active_config = None
- if "trigger" not in st.session_state:
- st.session_state.trigger = False
- if "item_id" not in st.session_state:
- st.session_state.item_id = None
-
- col1, col2, col3 = st.columns(3)
-
- configs = json.loads(requests.get(url_config).text)
-
- active_config_index = 0
- if st.session_state.active_config:
- active_config_name = st.session_state.active_config.get('name')
- active_config_index = next((index for (index, config) in enumerate(configs.values()) if config["name"] == active_config_name), 0)
- option = col1.selectbox("Select an option", tuple(configs), index=active_config_index, label_visibility="collapsed")
-
- if col2.button("Active", use_container_width=True):
- st.session_state.item_id = None
- body = {
- "config_name": option
- }
- requests.post(url=url_active_config, json=body)
- st.session_state.active_config = json.loads(requests.get(url_active_config).text)
-
- if st.session_state.active_config:
- active_config_name = st.session_state.active_config.get('name')
- col2.write(f"active config: {active_config_name}")
-
-
- if st.session_state.active_config:
- if col3.button("Trigger", use_container_width=True):
- st.session_state.trigger = True
- response = requests.post(url_trigger)
- item_id = response.json().get("item_id")
- st.session_state.item_id = item_id
- col3.write(f"item id: {item_id}")
-
- # TODO: Add camera inputs
-
- columns = st.columns(2)
-
- if st.session_state.item_id and (st.session_state.active_config is not None):
-
- time.sleep(5)
-
- url_metadata = URL_ORCH + f"items/{st.session_state.item_id}"
- response = requests.get(url_metadata)
- metadata = response.json()
- decision = metadata["decision"]
- inferences = metadata["inferences"]
-
- print("decision", decision)
- print("inferences", inferences)
-
- cameras = st.session_state.active_config["cameras"]
- for i, camera in enumerate(cameras):
- url_binaries = URL_ORCH + f"items/{st.session_state.item_id}/binaries/{camera}"
- response = requests.get(url_binaries)
- image = response.content
- # If metadata is not empty, we plot the predictions
- if filtering_items_that_have_predictions(metadata, camera):
- image = Image.open(BytesIO(image))
- image = plot_predictions(image, camera, metadata)
- columns[i].image(image, channels="BGR", width=450)
- if inferences.get(camera):
- columns[i].markdown(inferences[camera])
-
- st.markdown(
- f"{decision}
",
- unsafe_allow_html=True,
- )
-
- # TODO: add prediction on picture
-
-# Exécution du script principal
-if __name__ == "__main__":
- main()
diff --git a/edge_streamlit/app.py b/edge_streamlit/app.py
index 548925ba..fd69e7ab 100644
--- a/edge_streamlit/app.py
+++ b/edge_streamlit/app.py
@@ -1,100 +1,117 @@
-from utils import display_camera_checkboxes, list_cameras
-import streamlit as st
-import requests
import json
-import cv2
+import os
+import time
+import requests
+import streamlit as st
+from prediction_boxes import filtering_items_that_have_predictions, plot_predictions
+from PIL import Image
+from io import BytesIO
# Page configuration
-st.set_page_config(
- page_title="Mon Application Streamlit",
- page_icon="🔦",
- layout="wide"
-)
+st.set_page_config(page_title="VIO-edge", page_icon="🔦", layout="wide")
-# Page content
-st.title("VIO Edge")
+URL_ORCH = os.getenv("ORCHESTRATOR_URL", "http://localhost:8000/api/v1/")
-URL_ORCH = "http://localhost:8000/api/v1/"
url_config = URL_ORCH + "configs"
url_active_config = URL_ORCH + "configs/active"
url_trigger = URL_ORCH + "trigger"
+
def main():
"""
Fonction principale de l'application Streamlit.
"""
# Init variables
- if "recording" not in st.session_state:
- st.session_state.recording = False
- if "selected_cameras" not in st.session_state:
- st.session_state.selected_cameras = []
+ active_config = json.loads(requests.get(url_active_config).text)
+ if active_config:
+ st.session_state.active_config = active_config
+
+ if "active_config" not in st.session_state:
+ st.session_state.active_config = None
if "trigger" not in st.session_state:
st.session_state.trigger = False
- if "image" not in st.session_state:
- st.session_state.image = None
-
- col_1, col_2 = st.columns(2)
+ if "item_id" not in st.session_state:
+ st.session_state.item_id = None
- configs = json.loads(requests.get(url_config).text)
+ col1, col2, col3 = st.columns(3)
- option = col_1.selectbox("Select an option", tuple(configs), label_visibility="collapsed")
+ configs = json.loads(requests.get(url_config).text)
- if col_2.button("Active Config"):
- body = {
- "config_name": option
- }
+ active_config_index = 0
+ if st.session_state.active_config:
+ active_config_name = st.session_state.active_config.get("name")
+ active_config_index = next(
+ (
+ index
+ for (index, config) in enumerate(configs.values())
+ if config["name"] == active_config_name
+ ),
+ 0,
+ )
+ option = col1.selectbox(
+ "Select an option",
+ tuple(configs),
+ index=active_config_index,
+ label_visibility="collapsed",
+ )
+
+ if col2.button("Active", use_container_width=True):
+ st.session_state.item_id = None
+ body = {"config_name": option}
requests.post(url=url_active_config, json=body)
- active_config = None
- active_config = json.loads(requests.get(url_active_config).text).get("name")
- col_2.write(f"active config: {active_config}" )
-
- # Sidebar parameters
- st.sidebar.title("Configuration")
- available_cameras = list_cameras()
- selected_cameras = display_camera_checkboxes(available_cameras)
- st.session_state.selected_cameras = selected_cameras
-
- if st.sidebar.button("Start/Stop Recording"):
- st.session_state.recording = not st.session_state.recording
-
- if st.button("Trigger"):
- st.session_state.trigger = True
- response = requests.post(url_trigger)
- item_id = response.json().get("item_id")
- st.subheader(item_id)
-
- # Video capture logic
- if st.session_state.recording and selected_cameras:
- caps = {index: cv2.VideoCapture(index) for index in selected_cameras}
- columns = st.columns(len(selected_cameras))
- frames_video = {index: columns[i].empty() for i, index in enumerate(selected_cameras)}
-
- while st.session_state.recording:
- for index in selected_cameras:
- ret, frame = caps[index].read()
- if st.session_state.trigger:
- st.session_state.image = frame
-
- if ret:
- frames_video[index].image(frame, channels="BGR")
- else:
- frames_video[index].text(f"Camera {index} - Failed to capture video")
-
- if st.session_state.image is not None and st.session_state.trigger:
- columns[index].image(st.session_state.image , channels="BGR")
- # Convertir le tableau NumPy en bytes
- # _, buffer = cv2.imencode('.jpg', st.session_state.image)
- # img_byte_arr = BytesIO(buffer)
- # response = requests.post(url_trigger, files={"image": ("filename", img_byte_arr, "image/jpeg")})
- # print(response.text)
- # columns[index].write(response.text)
-
- st.session_state.trigger = False
-
- for cap in caps.values():
- cap.release()
-
-
+ st.session_state.active_config = json.loads(
+ requests.get(url_active_config).text
+ )
+
+ if st.session_state.active_config:
+ active_config_name = st.session_state.active_config.get("name")
+ col2.write(f"active config: {active_config_name}")
+
+ if st.session_state.active_config:
+ if col3.button("Trigger", use_container_width=True):
+ st.session_state.trigger = True
+ response = requests.post(url_trigger)
+ item_id = response.json().get("item_id")
+ st.session_state.item_id = item_id
+ col3.write(f"item id: {item_id}")
+
+ # TODO: Add camera inputs
+
+ columns = st.columns(2)
+
+ if st.session_state.item_id and (st.session_state.active_config is not None):
+ time.sleep(5)
+
+ url_metadata = URL_ORCH + f"items/{st.session_state.item_id}"
+ response = requests.get(url_metadata)
+ metadata = response.json()
+ decision = metadata["decision"]
+ inferences = metadata["inferences"]
+
+ print("decision", decision)
+ print("inferences", inferences)
+
+ cameras = st.session_state.active_config["cameras"]
+ for i, camera in enumerate(cameras):
+ url_binaries = (
+ URL_ORCH + f"items/{st.session_state.item_id}/binaries/{camera}"
+ )
+ response = requests.get(url_binaries)
+ image = response.content
+ # If metadata is not empty, we plot the predictions
+ if filtering_items_that_have_predictions(metadata, camera):
+ image = Image.open(BytesIO(image))
+ image = plot_predictions(image, camera, metadata)
+ columns[i].image(image, channels="BGR", width=450)
+ if inferences.get(camera):
+ columns[i].markdown(inferences[camera])
+
+ st.markdown(
+ f"{decision}
",
+ unsafe_allow_html=True,
+ )
+
+ # TODO: add prediction on picture
# Exécution du script principal
diff --git a/edge_streamlit/utils.py b/edge_streamlit/utils.py
deleted file mode 100644
index a5398ce7..00000000
--- a/edge_streamlit/utils.py
+++ /dev/null
@@ -1,44 +0,0 @@
-import logging
-from typing import List
-
-import cv2
-import streamlit as st
-
-logger = logging.getLogger(__name__)
-logger.addHandler(logging.StreamHandler())
-logger.setLevel(logging.DEBUG)
-
-
-def list_cameras() -> List[str]:
- """
- Liste toutes les caméras disponibles sur le système.
- """
- logger.info("Listing available cameras")
- index = 0
- available_cameras = []
- while True:
- cap = cv2.VideoCapture(index)
- if cap.isOpened():
- available_cameras.append(f"Cam {index}")
- else:
- break
- cap.release()
- index += 1
- logger.debug(f"{len(available_cameras)} cameras found")
- return available_cameras
-
-
-def display_camera_checkboxes(available_cameras: List[str]) -> List[int]:
- """
- Affiche les caméras disponibles sous forme de cases à cocher.
- Retourne les indices des caméras sélectionnées.
- """
- selected_cameras = []
- if len(available_cameras) == 0:
- st.warning("No camera detected.")
- else:
- for i, camera_name in enumerate(available_cameras):
- if st.sidebar.checkbox(camera_name, key=f"camera_{i}"):
- selected_cameras.append(i)
- logger.debug(f"Selected cameras are {selected_cameras}")
- return selected_cameras