Duplicate from konglong/yolov8_demo

Co-authored-by: zhiwei <[email protected]>

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README.md

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+---
+title: Yolov8 Demo
+emoji: 📊
+colorFrom: blue
+colorTo: yellow
+sdk: gradio
+sdk_version: 3.29.0
+app_file: app.py
+pinned: false
+duplicated_from: konglong/yolov8_demo
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import gradio as gr 
+import pandas as pd 
+
+from PIL import Image
+from torchkeras import plots 
+from torchkeras.data import get_url_img
+
+from pathlib import Path
+from ultralytics import YOLO
+import ultralytics
+from ultralytics.yolo.data import utils 
+
+model = YOLO('yolov8n.pt')
+
+
+#load class_names
+yaml_path = str(Path(ultralytics.__file__).parent/'datasets/coco128.yaml') 
+class_names = utils.yaml_load(yaml_path)['names']
+
+def detect(img):
+    if isinstance(img,str):
+        img = get_url_img(img) if img.startswith('http') else Image.open(img).convert('RGB')
+    result = model.predict(source=img)
+    if len(result[0].boxes.boxes)>0:
+        vis = plots.plot_detection(img,boxes=result[0].boxes.boxes,
+                     class_names=class_names, min_score=0.2)
+    else:
+        vis = img
+    return vis
+
+with gr.Blocks() as demo:
+
+    with gr.Tab("Webcam"):
+        input_img = gr.Image(source='webcam',type='pil')
+        button = gr.Button("Detect",variant="primary")
+        
+        gr.Markdown("## Output")
+        out_img = gr.Image(type='pil')
+        
+        button.click(detect,
+                     inputs=input_img, 
+                     outputs=out_img)
+        
+    with gr.Tab("Url"):
+        default_url = 'https://t7.baidu.com/it/u=3601447414,1764260638&fm=193&f=GIF'
+        url = gr.Textbox(value=default_url)
+        button = gr.Button("Detect",variant="primary")
+        
+        gr.Markdown("## Output")
+        out_img = gr.Image(type='pil')
+        
+        button.click(detect,
+                     inputs=url, 
+                     outputs=out_img)
+        
+    with gr.Tab("Upload"):
+        input_img = gr.Image(type='pil')
+        button = gr.Button("Detect",variant="primary")
+        
+        gr.Markdown("## Output")
+        out_img = gr.Image(type='pil')
+        
+        button.click(detect,
+                     inputs=input_img, 
+                     outputs=out_img)
+        
+
+        
+gr.close_all() 
+demo.queue()
+demo.launch()

requirements.txt

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+ultralytics
+scikit-image
+torchkeras
+pathlib
+torch
+accelerate