Add colab template and minor fixes (#137)

Co-authored-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

docs/index.md

@@ -1,6 +1,16 @@
-# Welcome to Ultralytics YOLO
-
-Welcome to the Ultralytics YOLO documentation landing page! Ultralytics YOLOv8 is the latest version of the YOLO (You
+<div align="center">
+  <a href="https://ultralytics.com/yolov5" target="_blank">
+    <img width="1024" src="https://user-images.githubusercontent.com/26833433/210431393-39c997b8-92a7-4957-864f-1f312004eb54.png"></a>
+<br>
+  <a href="https://bit.ly/yolov5-paperspace-notebook"><img src="https://assets.paperspace.io/img/gradient-badge.svg" alt="Run on Gradient"></a>
+  <a href="https://colab.research.google.com/github/glenn-jocher/glenn-jocher.github.io/blob/main/tutorial.ipynb"><img src="https://colab.research.google.com/assets/colab-badge.svg" alt="Open In Colab"></a>
+  <a href="https://www.kaggle.com/ultralytics/yolov5"><img src="https://kaggle.com/static/images/open-in-kaggle.svg" alt="Open In Kaggle"></a>
+<br>
+</div>
+
+# Welcome to Ultralytics YOLOv8
+
+Welcome to the Ultralytics YOLOv8 documentation landing page! Ultralytics YOLOv8 is the latest version of the YOLO (You
 Only Look Once) object detection and image segmentation model developed by Ultralytics. This page serves as the starting
 point for exploring the various resources available to help you get started with YOLOv8 and understand its features and
 capabilities.

ultralytics/yolo/configs/default.yaml

@@ -47,7 +47,7 @@ dnn: False # use OpenCV DNN for ONNX inference
 plots: True # show plots during training
 
 # Prediction settings --------------------------------------------------------------------------------------------------
-source: "ultralytics/assets" # source directory for images or videos
+source: null # source directory for images or videos
 show: False # show results if possible
 save_txt: False # save results as .txt file
 save_conf: False # save results with confidence scores

ultralytics/yolo/engine/model.py

@@ -224,4 +224,5 @@ class YOLO:
         args.pop("device", None)
         args.pop("project", None)
         args.pop("name", None)
-        args.pop("batch_size", None)
+        args.pop("batch", None)
+        args.pop("epochs", None)

ultralytics/yolo/v8/detect/predict.py

@@ -2,7 +2,7 @@ import hydra
 import torch
 
 from ultralytics.yolo.engine.predictor import BasePredictor
-from ultralytics.yolo.utils import DEFAULT_CONFIG, ops
+from ultralytics.yolo.utils import DEFAULT_CONFIG, ROOT, ops
 from ultralytics.yolo.utils.checks import check_imgsz
 from ultralytics.yolo.utils.plotting import Annotator, colors, save_one_box
 
@@ -83,8 +83,9 @@ class DetectionPredictor(BasePredictor):
 
 @hydra.main(version_base=None, config_path=str(DEFAULT_CONFIG.parent), config_name=DEFAULT_CONFIG.name)
 def predict(cfg):
-    cfg.model = cfg.model or "n.pt"
+    cfg.model = cfg.model or "yolov8n.pt"
     cfg.imgsz = check_imgsz(cfg.imgsz, min_dim=2)  # check image size
+    cfg.source = cfg.source or ROOT / "assets"
     predictor = DetectionPredictor(cfg)
     predictor()