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Change image url for fake diffusion demos (#3120)

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* Change image url
:

* Fix demos

* CHANGELOG

* Use s3 link
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Freddy Boulton 2023-02-03 11:21:41 -05:00 committed by GitHub
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6 changed files with 5 additions and 6 deletions
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CHANGELOG.md
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@ -27,7 +27,7 @@ No changes to highlight.
No changes to highlight.
## Full Changelog:
No changes to highlight.
- Changed URL of final image for `fake_diffusion` demos by [@freddyaboulton](https://github.com/freddyaboulton) in [PR 3120](https://github.com/gradio-app/gradio/pull/3120)
## Contributors Shoutout:

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demo/fake_diffusion/run.ipynb
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@ -1 +1 @@
{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: fake_diffusion\n", "### This demo uses a fake model to showcase iterative output. The Image output will update every time a generator is returned until the final image.\n", " "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "\n", "# define core fn, which returns a generator {steps} times before returning the image\n", "def fake_diffusion(steps):\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = np.random.random((600, 600, 3))\n", " yield image\n", "\n", " image = \"https://i.picsum.photos/id/867/600/600.jpg?hmac=qE7QFJwLmlE_WKI7zMH6SgH5iY5fx8ec6ZJQBwKRT44\"\n", " yield image\n", "\n", "\n", "demo = gr.Interface(fake_diffusion, inputs=gr.Slider(1, 10, 3), outputs=\"image\")\n", "\n", "# define queue - required for generators\n", "demo.queue()\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: fake_diffusion\n", "### This demo uses a fake model to showcase iterative output. The Image output will update every time a generator is returned until the final image.\n", " "]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio numpy "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "\n", "# define core fn, which returns a generator {steps} times before returning the image\n", "def fake_diffusion(steps):\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = np.random.random((600, 600, 3))\n", " yield image\n", " image = \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\"\n", " yield image\n", "\n", "\n", "demo = gr.Interface(fake_diffusion, inputs=gr.Slider(1, 10, 3), outputs=\"image\")\n", "\n", "# define queue - required for generators\n", "demo.queue()\n", "\n", "demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

3
demo/fake_diffusion/run.py
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@ -8,8 +8,7 @@ def fake_diffusion(steps):
time.sleep(1)
image = np.random.random((600, 600, 3))
yield image
image = "https://i.picsum.photos/id/867/600/600.jpg?hmac=qE7QFJwLmlE_WKI7zMH6SgH5iY5fx8ec6ZJQBwKRT44"
image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg"
yield image

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demo/fake_diffusion_with_gif/image.gif
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demo/fake_diffusion_with_gif/run.ipynb
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@ -1 +1 @@
{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: fake_diffusion_with_gif"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/fake_diffusion_with_gif/image.gif"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "import os\n", "from PIL import Image\n", "import requests\n", "from io import BytesIO\n", "\n", "\n", "def create_gif(images):\n", " pil_images = []\n", " for image in images:\n", " if isinstance(image, str):\n", " response = requests.get(image)\n", " image = Image.open(BytesIO(response.content))\n", " else:\n", " image = Image.fromarray((image * 255).astype(np.uint8))\n", " pil_images.append(image)\n", " fp_out = os.path.join(os.path.abspath(''), \"image.gif\")\n", " img = pil_images.pop(0)\n", " img.save(fp=fp_out, format='GIF', append_images=pil_images,\n", " save_all=True, duration=400, loop=0)\n", " return fp_out\n", "\n", "\n", "def fake_diffusion(steps):\n", " images = []\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = np.random.random((600, 600, 3))\n", " images.append(image)\n", " yield image, gr.Image.update(visible=False)\n", " \n", " time.sleep(1)\n", " image = \"https://i.picsum.photos/id/867/600/600.jpg?hmac=qE7QFJwLmlE_WKI7zMH6SgH5iY5fx8ec6ZJQBwKRT44\" \n", " images.append(image)\n", " gif_path = create_gif(images)\n", " \n", " yield image, gr.Image.update(value=gif_path, visible=True)\n", "\n", "\n", "demo = gr.Interface(fake_diffusion, \n", " inputs=gr.Slider(1, 10, 3), \n", " outputs=[\"image\", gr.Image(label=\"All Images\", visible=False)])\n", "demo.queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
{"cells": [{"cell_type": "markdown", "id": 302934307671667531413257853548643485645, "metadata": {}, "source": ["# Gradio Demo: fake_diffusion_with_gif"]}, {"cell_type": "code", "execution_count": null, "id": 272996653310673477252411125948039410165, "metadata": {}, "outputs": [], "source": ["!pip install -q gradio "]}, {"cell_type": "code", "execution_count": null, "id": 288918539441861185822528903084949547379, "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/fake_diffusion_with_gif/image.gif"]}, {"cell_type": "code", "execution_count": null, "id": 44380577570523278879349135829904343037, "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "import numpy as np\n", "import time\n", "import os\n", "from PIL import Image\n", "import requests\n", "from io import BytesIO\n", "\n", "\n", "def create_gif(images):\n", " pil_images = []\n", " for image in images:\n", " if isinstance(image, str):\n", " response = requests.get(image)\n", " image = Image.open(BytesIO(response.content))\n", " else:\n", " image = Image.fromarray((image * 255).astype(np.uint8))\n", " pil_images.append(image)\n", " fp_out = os.path.join(os.path.abspath(''), \"image.gif\")\n", " img = pil_images.pop(0)\n", " img.save(fp=fp_out, format='GIF', append_images=pil_images,\n", " save_all=True, duration=400, loop=0)\n", " return fp_out\n", "\n", "\n", "def fake_diffusion(steps):\n", " images = []\n", " for _ in range(steps):\n", " time.sleep(1)\n", " image = np.random.random((600, 600, 3))\n", " images.append(image)\n", " yield image, gr.Image.update(visible=False)\n", " \n", " time.sleep(1)\n", " image = \"https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg\" \n", " images.append(image)\n", " gif_path = create_gif(images)\n", " \n", " yield image, gr.Image.update(value=gif_path, visible=True)\n", "\n", "\n", "demo = gr.Interface(fake_diffusion, \n", " inputs=gr.Slider(1, 10, 3), \n", " outputs=[\"image\", gr.Image(label=\"All Images\", visible=False)])\n", "demo.queue()\n", "\n", "if __name__ == \"__main__\":\n", " demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

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demo/fake_diffusion_with_gif/run.py
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@ -32,7 +32,7 @@ def fake_diffusion(steps):
yield image, gr.Image.update(visible=False)
time.sleep(1)
image = "https://i.picsum.photos/id/867/600/600.jpg?hmac=qE7QFJwLmlE_WKI7zMH6SgH5iY5fx8ec6ZJQBwKRT44"
image = "https://gradio-builds.s3.amazonaws.com/diffusion_image/cute_dog.jpg"
images.append(image)
gif_path = create_gif(images)