Initial commit.

.gitignore

@@ -0,0 +1,6 @@
+.idea/
+venv/
+flagged/
+*.jpg
+*.png
+*.db

README.md

@@ -1,8 +1,8 @@
 ---
-title: Yolo V5
-emoji: 📈
-colorFrom: green
-colorTo: blue
+title: YOLOv5
+emoji: 🤙
+colorFrom: purple
+colorTo: pink
 sdk: gradio
 app_file: app.py
 pinned: false

app.py

@@ -0,0 +1,32 @@
+import gradio as gr
+import torch
+
+
+title = "Object Detection with YOLOv5"
+description = "Detect objects in images with YOLOv5 (You Only Look Once v5)"
+article = "<p style='text-align: center'><a href='https://news.machinelearning.sg/posts/object_detection_with_yolov5/'>Blog</a> | <a href='https://github.com/eugenesiow/practical-ml'>Github Repo</a></p>"
+
+
+def inference(img):
+    results = model([img], size=640)
+    results.render()
+    return results.imgs[0]
+
+
+torch.hub.download_url_to_file('https://images.unsplash.com/photo-1526497127495-3b388dc87620?auto=format&fit=crop&w=640&q=80',
+                               'baseball.jpg')
+torch.hub.download_url_to_file('https://images.unsplash.com/photo-1608278047522-58806a6ac85b?auto=format&fit=crop&w=640&q=80', 'hulk.jpg')
+model = torch.hub.load('ultralytics/yolov5', 'yolov5s')
+
+
+gr.Interface(
+    inference,
+    gr.inputs.Image(type="pil", label="Input"),
+    gr.outputs.Image(type="pil", label="Output"),
+    title=title,
+    description=description,
+    article=article,
+    examples=[['baseball.jpg'], ['hulk.jpg']],
+    enable_queue=True,
+    allow_flagging=False,
+).launch(debug=False)

packages.txt

@@ -0,0 +1,4 @@
+python3-opencv
+ffmpeg
+libsm6
+libxext6

requirements.txt

@@ -0,0 +1,7 @@
+opencv-python==4.5.4.58
+pyaml==21.10.1
+PyYAML==6.0
+seaborn==0.11.2
+torch==1.10.0
+torchvision==0.11.1
+tqdm==4.62.3