Spaces:
Sleeping
Sleeping
File size: 2,030 Bytes
5f810af fc6731e 5f810af fc6731e 5f810af fc6731e 5f810af fc6731e 5f810af fc6731e 5f810af fc6731e 5f810af fc6731e 5f810af d7cfb5c |
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 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 |
import os
import urllib.request
import numpy as np
import cv2
from ultralytics import YOLO
import gradio as gr
# --- Setup writable paths for YOLO ---
os.environ["YOLO_CONFIG_DIR"] = "/tmp"
os.environ["HOME"] = "/tmp"
# --- Download YOLOv8s weights if not already present ---
MODEL_PATH = "/tmp/yolov8s.pt"
if not os.path.exists(MODEL_PATH):
print("Downloading YOLOv8s weights...")
urllib.request.urlretrieve(
"https://github.com/ultralytics/assets/releases/download/v8.3.0/yolov8s.pt",
MODEL_PATH
)
# --- Load the YOLOv8 model ---
model = YOLO(MODEL_PATH)
# --- Detection function ---
def detect_objects(image):
"""
Input: image in BGR format (from Gradio/OpenCV)
Output: annotated image, detected object names
"""
# Convert BGR to RGB for YOLO
image_rgb = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
# Run YOLO inference directly on RGB image
results = model(image_rgb, conf=0.25) # confidence threshold 25%
# Annotated image (YOLO expects RGB, but plot returns RGB)
annotated_image = results[0].plot()
# Convert annotated image back to BGR for OpenCV/Gradio display
annotated_bgr = cv2.cvtColor(annotated_image, cv2.COLOR_RGB2BGR)
# Extract detected object names
if results[0].boxes is not None:
detected_classes = [model.names[int(c)] for c in results[0].boxes.cls]
detected_text = ", ".join(detected_classes) if detected_classes else "No objects detected"
else:
detected_text = "No objects detected"
return annotated_bgr, detected_text
# --- Gradio Interface ---
demo = gr.Interface(
fn=detect_objects,
inputs=gr.Image(type="numpy", label="Upload Image"),
outputs=[
gr.Image(type="numpy", label="Detected Objects"),
gr.Textbox(label="Objects Detected")
],
title="🧠 Object Detection App",
description="Upload an image — YOLOv8s detects all objects and lists their names!"
)
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860)
|