HongChuang/ultralytics-ascend
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ultralytics 8.3.16 PyTorch 2.5.0 support (#16998)

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Signed-off-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
Co-authored-by: RizwanMunawar <chr043416@gmail.com>
Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
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Glenn Jocher 2024-10-18 13:54:45 +02:00 • committed by GitHub
parent ef28f1078c
commit 8d7d1fe390
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17 changed files with 570 additions and 144 deletions
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5
ultralytics/solutions/streamlit_inference.py
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@ -11,7 +11,7 @@ from ultralytics.utils.downloads import GITHUB_ASSETS_STEMS
def inference(model=None):
"""Runs real-time object detection on video input using Ultralytics YOLO11 in a Streamlit application."""
"""Performs real-time object detection on video input using YOLO in a Streamlit web application."""
check_requirements("streamlit>=1.29.0") # scope imports for faster ultralytics package load speeds
import streamlit as st
@ -108,7 +108,7 @@ def inference(model=None):
st.warning("Failed to read frame from webcam. Please make sure the webcam is connected properly.")
break
prev_time = time.time()
prev_time = time.time() # Store initial time for FPS calculation
# Store model predictions
if enable_trk == "Yes":
@ -120,7 +120,6 @@ def inference(model=None):
# Calculate model FPS
curr_time = time.time()
fps = 1 / (curr_time - prev_time)
prev_time = curr_time
# display frame
org_frame.image(frame, channels="BGR")