Fix coordinate system conventions in renderer

Summary:
## Updates

- Defined the world and camera coordinates according to this figure. The world coordinates are defined as having +Y up, +X left and +Z in.

{F230888499}

- Removed all flipping from blending functions.
- Updated the rasterizer to return images with +Y up and +X left.
- Updated all the mesh rasterizer tests
    - The expected values are now defined in terms of the default +Y up, +X left
    - Added tests where the triangles in the meshes are non symmetrical so that it is clear which direction +X and +Y are

## Questions:
- Should we have **scene settings** instead of raster settings?
    - To be more correct we should be [z clipping in the rasterizer based on the far/near clipping planes](https://github.com/ShichenLiu/SoftRas/blob/master/soft_renderer/cuda/soft_rasterize_cuda_kernel.cu#L400) - these values are also required in the blending functions so should we make these scene level parameters and have a scene settings tuple which is available to the rasterizer and shader?

Reviewed By: gkioxari

Differential Revision: D20208604

fbshipit-source-id: 55787301b1bffa0afa9618f0a0886cc681da51f3

tests/test_blending.py

@@ -41,7 +41,7 @@ def sigmoid_blend_naive_loop(colors, fragments, blend_params):
                 pixel_colors[n, h, w, :3] = colors[n, h, w, 0, :]
                 pixel_colors[n, h, w, 3] = 1.0 - alpha
 
-    return torch.flip(pixel_colors, [1])
+    return pixel_colors
 
 
 def sigmoid_blend_naive_loop_backward(
@@ -54,8 +54,6 @@ def sigmoid_blend_naive_loop_backward(
     N, H, W, K = pix_to_face.shape
     device = pix_to_face.device
     grad_distances = torch.zeros((N, H, W, K), dtype=dists.dtype, device=device)
-    images = torch.flip(images, [1])
-    grad_images = torch.flip(grad_images, [1])
 
     for n in range(N):
         for h in range(H):
@@ -130,7 +128,7 @@ def softmax_blend_naive(colors, fragments, blend_params):
                 pixel_colors[n, h, w, :3] += (delta / denom) * bk_color
                 pixel_colors[n, h, w, 3] = 1.0 - alpha
 
-    return torch.flip(pixel_colors, [1])
+    return pixel_colors
 
 
 class TestBlending(unittest.TestCase):