I am studying an undergraduate course in number theory. In order to prove Minkowski's Theorem, we define convex subsets of $\mathbb{R}^2$:
A subset $X \in \mathbb{R}^2$ is convex if, for any $p, q \in X$, $\lambda p + (1 - \lambda) q \in X$ for all $\lambda \in [0; 1]$.
As it's $\mathbb{R}^2$, it seems like we can visualize this by imagining any subset of $\mathbb{R}^2$ that doesn't somehow "go back in on itself", and that's what convex is. Basically, the classical notion of convex.
Are there any exceptions to this? Is it safe, if I visualize any subset of $\mathbb{R}^2$, and it "looks" convex in this sense, to assume that it is - without an analytical proof?
Out of curiosity - if we parameterised a closed curve $\gamma: I \rightarrow \mathbb{R}^2$ with no self-intersections, and considered our subset of $\mathbb{R}^2$ to be the shape it encloses, would we be able to say something about the subset it encloses (whether or not it is convex) based on the oriented curvature of the curve?