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afb7dac | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 | import streamlit as st
from ultralytics import YOLO
from PIL import Image
import numpy as np
import cv2
st.set_page_config(page_title="OceanCV Object Detection", page_icon="🦑")
st.title("OceanCV FirstPass Detector")
st.write("Upload marine imagery to detect underwater objects.")
@st.cache_resource
def load_model():
return YOLO("OceanCV_FirstPass.pt")
model = load_model()
uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "jpeg", "png"])
conf = st.slider("Confidence Threshold", 0.1, 1.0, 0.5)
iou = st.slider("IOU Threshold", 0.1, 1.0, 0.45)
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption="Uploaded Image", use_column_width=True)
if st.button("Detect Objects"):
with st.spinner("Analyzing..."):
results = model.predict(image, conf=conf, iou=iou, imgsz=1024)
res_plotted = results[0].plot()
res_rgb = cv2.cvtColor(res_plotted, cv2.COLOR_BGR2RGB)
st.image(res_rgb, caption="Processed Image", use_column_width=True)
st.write(f"Detected {len(results[0].boxes)} objects.")
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