docs: version 0.5.1

R3gm · Oct 10, 2024 · d994479 · d994479
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diff --git a/README.md b/README.md
@@ -6,7 +6,7 @@ The goal of this project is to make Stable Diffusion more accessible, simple and
 
 **Installation:**
 ```
-pip install stablepy==0.5.0
+pip install stablepy==0.5.1
 ```
 
 **Usage:**
@@ -37,7 +37,7 @@ model = Model_Diffusers(
     task_name= 'txt2img',
 )
 
-image, path_image = model(
+image, info_image = model(
     prompt='highly detailed portrait of an underwater city, with towering spires and domes rising up from the ocean floor',
     num_steps = 30,
     guidance_scale = 7.5,
@@ -61,7 +61,7 @@ model = Model_Diffusers(
     task_name= 'canny',
 )
 
-images, path_images = model(
+images, info_image = model(
     prompt='highly detailed portrait of an underwater city, with towering spires and domes rising up from the ocean floor',
     num_steps = 30,
     image_resolution = 768,
@@ -78,9 +78,14 @@ images, path_images = model(
 
 images[1]
 ```
-**📖 News:**
+**📖 New Update Details:**
 
-🔥 Version 0.5.0: New Update Details
+🔥 Version 0.5.1:
+
+- After generation, PIL images are now returned along with sublists containing the seeds, image paths, and metadata with the parameters used in generation. `[pil_image], [seed, image_path, metadata]`
+- The use of `image_previews=True` has been improved, and now preview images can be obtained during the generation steps using a generator. For more details, refer to the Colab notebook.
+
+🔥 Version 0.5.0:
 
 - Fix LoRA SDXL compatibility.
 - Latent upscaler and variants.
@@ -90,7 +95,7 @@ images[1]
 - ControlNet "lineart_anime" task accessible and able to load a model different from the "lineart" task.
 - ControlNet Tile and Recolor for SD1.5 and SDXL ("tile" replaces the previous task called "sdxl_tile_realistic").
 
-🔥 Version 0.4.0: New Update Details
+🔥 Version 0.4.0:
 
 - IP Adapter with the variants FaceID and Instant-Style
 - New samplers

diff --git a/pyproject.toml b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "stablepy"
-version = "0.5.0"
+version = "0.5.1"
 description = "A tool for easy use of stable diffusion"
 authors = ["Roger Condori(R3gm) <[email protected]>"]
 readme = "README.md"

diff --git a/stablepy/__version__.py b/stablepy/__version__.py
@@ -1 +1 @@
-__version__ = "0.5.0"
+__version__ = "0.5.1"
diff --git a/stablepy_demo.ipynb b/stablepy_demo.ipynb
@@ -3,8 +3,8 @@
     {
       "cell_type": "markdown",
       "metadata": {
-        "id": "view-in-github",
-        "colab_type": "text"
+        "colab_type": "text",
+        "id": "view-in-github"
       },
       "source": [
         "<a href=\"https://colab.research.google.com/github/R3gm/stablepy/blob/main/stablepy_demo.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
@@ -36,7 +36,7 @@
       },
       "outputs": [],
       "source": [
-        "!pip install stablepy==0.5.0 -q"
+        "!pip install stablepy==0.5.1 -q"
       ]
     },
     {
@@ -309,26 +309,26 @@
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "V0-kKkqzbLwa"
+      },
       "source": [
         "The upscaler_model_path can be used with different ESRGAN models and can also be used with Lanczos, Nearest, or the variants of latent upscaler.\n",
         "Example: `upscaler_model_path=\"Latent (bicubic)\",`"
-      ],
-      "metadata": {
-        "id": "V0-kKkqzbLwa"
-      }
+      ]
     },
     {
       "cell_type": "code",
+      "execution_count": null,
+      "metadata": {
+        "id": "Pc6cjdVfeOWM"
+      },
+      "outputs": [],
       "source": [
         "from stablepy import LATENT_UPSCALERS\n",
         "\n",
         "list(LATENT_UPSCALERS)"
-      ],
-      "metadata": {
-        "id": "Pc6cjdVfeOWM"
-      },
-      "execution_count": null,
-      "outputs": []
+      ]
     },
     {
       "cell_type": "markdown",
@@ -438,8 +438,8 @@
         "|canny|\"None\" \"Canny\"|\n",
         "|mlsd|\"None\" \"MLSD\"|\n",
         "| openpose | \"None\" \"Openpose\" |\n",
-        "|scribble|\"None\" \"HED\" \"Pidinet\"|\n",
-        "|softedge|\"None\" \"HED\" \"Pidinet\" \"HED safe\" \"Pidinet safe\"|\n",
+        "|scribble|\"None\" \"HED\" \"PidiNet\"|\n",
+        "|softedge|\"None\" \"HED\" \"PidiNet\" \"HED safe\" \"PidiNet safe\"|\n",
         "|segmentation|\"None\" \"UPerNet\"|\n",
         "|depth|\"None\" \"DPT\" \"Midas\"|\n",
         "|normalbae|\"None\" \"NormalBae\"|\n",
@@ -1062,6 +1062,9 @@
     },
     {
       "cell_type": "markdown",
+      "metadata": {
+        "id": "bF-15bKGT9W6"
+      },
       "source": [
         "- You can also use multiple images with a single IP adapter as follows by placing them in a list:\n",
         "\n",
@@ -1073,10 +1076,7 @@
         "    ip_adapter_mode = [\"original\"],\n",
         "```\n",
         "\n"
-      ],
-      "metadata": {
-        "id": "bF-15bKGT9W6"
-      }
+      ]
     },
     {
       "cell_type": "markdown",
@@ -1201,6 +1201,7 @@
         "model.load_pipe(\n",
         "    base_model_id = repo,\n",
         "    task_name = \"pattern\",\n",
+        "    retain_task_model_in_cache=False,\n",
         ")\n",
         "\n",
         "images, image_list = model(\n",
@@ -1215,6 +1216,92 @@
         "  display(image)"
       ]
     },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "# Displaying preview images during generation steps"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "model.load_pipe(\n",
+        "    base_model_id = repo,\n",
+        "    task_name = \"txt2img\",\n",
+        "    retain_task_model_in_cache=False,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "By setting `image_previews=True`, an iterable generator object for image previews will be created."
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "stream = model(\n",
+        "    prompt = \"a cat\",\n",
+        "    negative_prompt = \"worst quality\",\n",
+        "    sampler=\"DPM++ 2M SDE Lu\",\n",
+        "    img_width = 768,\n",
+        "    img_height = 768,\n",
+        "    image_previews=True,\n",
+        ")\n",
+        "\n",
+        "# Iterate over the generator object to get each value\n",
+        "for img, info_img in stream:\n",
+        "    display(img[0])\n",
+        "    if info_img[1]:\n",
+        "        print(info_img)"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "### Config the stream parameters\n"
+      ]
+    },
+    {
+      "cell_type": "code",
+      "execution_count": null,
+      "metadata": {},
+      "outputs": [],
+      "source": [
+        "model.stream_config(\n",
+        "    concurrency=2,\n",
+        "    latent_resize_by=1,\n",
+        "    vae_decoding=False,\n",
+        ")"
+      ]
+    },
+    {
+      "cell_type": "markdown",
+      "metadata": {},
+      "source": [
+        "- **concurrency**: `int`\n",
+        "  - **Default**: 5\n",
+        "  - **Description**: Controls how often the preview images are generated and displayed in relation to the steps. For example, a value of 2 displays an image every 2 steps.\n",
+        "\n",
+        "- **latent_resize_by**: `int`\n",
+        "  - **Default**: 8\n",
+        "  - **Description**: Controls the scaling size of the latent images. A value of 1 is useful for achieving high performance.\n",
+        "\n",
+        "- **vae_decoding**: `bool`\n",
+        "  - **Default**: `False`\n",
+        "  - **Description**: Use the VAE to decode the preview images. If set to `True`, it may negatively impact performance."
+      ]
+    },
     {
       "cell_type": "markdown",
       "metadata": {
@@ -1279,8 +1366,8 @@
     "accelerator": "GPU",
     "colab": {
       "gpuType": "T4",
-      "provenance": [],
-      "include_colab_link": true
+      "include_colab_link": true,
+      "provenance": []
     },
     "kernelspec": {
       "display_name": "Python 3",
@@ -1292,4 +1379,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}