using scipy and networkx

ConcaveHull.py

from scipy.spatial import Delaunay,ConvexHull
import networkx as nx

points = [ [0,0],[0,50],[50,50],[50,0],[0,400],[0,450],[50,400],[50,450],[700,300],[700,350],[750,300],[750,350],
          [900,600],[950,650],[950,600],[900,650]
]
def concave(points,alpha_x=150,alpha_y=250):
  points = [(i[0],i[1]) if type(i) <> tuple else i for i in points]
  de = Delaunay(points)
  dec = []
  a = alpha_x
  b = alpha_y
  for i in de.simplices:
      tmp = []
      j = [points[c] for c in i]
      if abs(j[0][1] - j[1][1]) > a or abs(j[1][1]-j[2][1]) > a or abs(j[0][1]-j[2][1]) > a or abs(j[0][0]-j[1][0]) > b or abs(j[1][0]-j[2][0]) > b or abs(j[0][0]-j[2][0]) > b:
          continue
      for c in i:
          tmp.append(points[c])
      dec.append(tmp)
  G = nx.Graph()
  for i in dec:
            G.add_edge(i[0], i[1])
            G.add_edge(i[0], i[2])
            G.add_edge(i[1], i[2])
  ret = []
  for graph in nx.connected_component_subgraphs(G):
        ch = ConvexHull(graph.nodes())
        tmp = []
        for i in ch.simplices:
            tmp.append(graph.nodes()[i[0]])
            tmp.append(graph.nodes()[i[1]])
        ret.append(tmp)
  return ret  
  #return [graph.nodes() for graph in nx.connected_component_subgraphs(G)] - all points inside the shape
concave(points)