From 544036b1e89d47b2c8131809cebe3c5a38d497b2 Mon Sep 17 00:00:00 2001
From: HugoTini <65409496+HugoTini@users.noreply.github.com>
Date: Sun, 7 Aug 2022 16:52:59 +0200
Subject: [PATCH] Update readme, remove cli

---
 cli.md          | 24 ---------------------
 deepbump_cli.py | 57 -------------------------------------------------
 readme.md       | 26 +++++++++-------------
 3 files changed, 10 insertions(+), 97 deletions(-)
 delete mode 100644 cli.md
 delete mode 100644 deepbump_cli.py

diff --git a/cli.md b/cli.md
deleted file mode 100644
index 52f72ba..0000000
--- a/cli.md
+++ /dev/null
@@ -1,24 +0,0 @@
-# Command line interface
-
-## Installation
-
-To use DeepBump from the terminal, you must have Python 
-installed as well as the following dependencies :
-
-    pip install onnxruntime
-    pip install Pillow
-
-By installing `onnxruntime`, be aware 
-of [Microsoft conditions](https://github.com/microsoft/onnxruntime/blob/master/docs/Privacy.md). This add-on use available APIs to disable telemetry.
-
-Then either [download DeepBump as a ZIP](https://github.com/HugoTini/DeepBump/releases) and extract it somewhere, or clone it with :
-
-    git clone https://github.com/HugoTini/DeepBump.git
-
-## Usage
-
-Go to the DeepBump folder, then use with :
-
-    python deepbump_cli.py -i <path_input_image> -n <path_generated_normal> -o <overlap>
-
-where `<overlap>` can be `small`, `medium` or `large`.
\ No newline at end of file
diff --git a/deepbump_cli.py b/deepbump_cli.py
deleted file mode 100644
index f4bdda1..0000000
--- a/deepbump_cli.py
+++ /dev/null
@@ -1,57 +0,0 @@
-from PIL import Image
-import numpy as np
-import utils_inference
-import onnxruntime as ort
-from argparse import ArgumentParser
-
-
-def progress_print(current, total):
-    print('{}/{}'.format(current, total))
-
-
-# Disable MS telemetry
-ort.disable_telemetry_events()
-
-# Parse cli arguments
-parser = ArgumentParser()
-parser.add_argument('-i', '--img_path', dest='img_path', required=True,
-                    help='path to the input image')
-parser.add_argument('-n', '--normal_path', dest='normal_path', required=True,
-                    help='path where the generated normal map is saved')
-parser.add_argument('-o', '--overlap', dest='overlap', required=True,
-                    help='tiles overlap size, must be "small", "medium" or "large"',
-                    choices=['small', 'medium', 'large'])
-args = parser.parse_args()
-
-# Load image
-img = np.array(Image.open(args.img_path)) / 255.0
-# Reshape to C,H,W
-img = np.transpose(img, (2, 0, 1))
-# Grayscale
-img = np.mean(img[0:3], axis=0, keepdims=True)
-
-# Split image in tiles
-print('tilling')
-tile_size = 256
-overlaps = {'small':  tile_size//6, 'medium':  tile_size//4,
-            'large': tile_size//2}
-stride_size = tile_size-overlaps[args.overlap]
-tiles, paddings = utils_inference.tiles_split(img, (tile_size, tile_size),
-                                    (stride_size, stride_size))
-
-# Predict tiles normal map
-print('generating')
-ort_session = ort.InferenceSession('./deepbump256.onnx')
-pred_tiles = utils_inference.tiles_infer(tiles, ort_session,
-                               progress_callback=progress_print)
-
-# Merge tiles
-print('merging')
-pred_img = utils_inference.tiles_merge(pred_tiles, (stride_size, stride_size),
-                             (3, img.shape[1], img.shape[2]),
-                             paddings)
-
-# Save image
-pred_img = pred_img.transpose((1, 2, 0))
-pred_img = Image.fromarray((pred_img*255.0).astype(np.uint8))
-pred_img.save(args.normal_path)
diff --git a/readme.md b/readme.md
index bfa7ace..b252ff6 100644
--- a/readme.md
+++ b/readme.md
@@ -2,35 +2,29 @@
 
 # DeepBump
 
-DeepBump is a tool to generate normal maps from single 
-pictures. See this [blog post](https://hugotini.github.io/deepbump) 
-for an introduction. It can be used either as a Blender add-on or 
-as a command-line program.
+DeepBump is a machine-learning driven tool to generate normal & height maps from single pictures. See this [blog post](https://hugotini.github.io/deepbump) for an introduction.
 
 # Installation
 
 1) [Download DeepBump as a ZIP](https://github.com/HugoTini/DeepBump/releases).
 
-2) In Blender, go to _Edit -> Preferences -> Add-ons -> Install_ 
-and select the downloaded ZIP file. Then enable the add-on.
+2) In Blender, go to _Edit -> Preferences -> Add-ons -> Install_ and select the downloaded ZIP file. Then enable the add-on.
 
-3) In the add-on preference, click the '_Install dependencies_' button (this 
-requires an internet connection and might take a while).
-
-By installing those dependencies, be aware of 
-[Microsoft conditions](https://github.com/microsoft/onnxruntime/blob/master/docs/Privacy.md). 
-This add-on use available APIs to disable telemetry.
+3) In the add-on preference, click the '_Install dependencies_' button (this requires an internet connection and might take a while).
 
+By installing those dependencies, be aware of [Microsoft conditions](https://github.com/microsoft/onnxruntime/blob/master/docs/Privacy.md). This add-on use available APIs to disable telemetry.
 
 # Usage
 
 Check the [blog post](https://hugotini.github.io/deepbump) first video.
 
-In the Shader Editor, select an _Image Texture Node_ and 
-click _Generate Normal Map_ in the right panel under 
-the _DeepBump_ tab.
+In the Shader Editor, in the right panel under the _DeepBump_ tab:
+
+**Color (albedo) → Normals** : Select a color image node and click _Generate Normal Map_.
+
+**Normals → Height (displacement)** : Select the generated normal map image node and click _Generate Height Map_.
 
-(For advanced usage, see [cli.md](cli.md) for the command-line interface.)
+**Normals → Curvature** : Select the generated normal map image node and click _Generate Curvature Map_.
 
 # License