From 608f7efa5e7e4b5fdf3a11550bc7bf2189aa9dd9 Mon Sep 17 00:00:00 2001
From: Mirko Birbaumer <mirko.birbaumer@hslu.ch>
Date: Sat, 3 Apr 2021 21:05:01 +0000
Subject: [PATCH] minor editing
---
...yter Notebook Block 6 - RNN and Image Captioning.ipynb | 8 +++-----
1 file changed, 3 insertions(+), 5 deletions(-)
diff --git a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb
index b5b726f..3d7051f 100644
--- a/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb
+++ b/notebooks/Block_6/Jupyter Notebook Block 6 - RNN and Image Captioning.ipynb
@@ -4106,8 +4106,7 @@
"\n",
"\n",
"Given an image like the example below, our goal is to generate a caption such as \"a surfer riding on a wave\".\n",
- "\n",
- "![alt text](./Bilder/surf.jpg \"Title\")"
+ "<img src=\"./Bilder/surf.jpg\" width=\"600\">\n"
]
},
{
@@ -4116,8 +4115,7 @@
"source": [
"To accomplish this, you'll use an attention-based model, which enables us to see what parts of the image the model focuses on as it generates a caption.\n",
"\n",
- "\n",
- "![alt text](./Bilder/imcap_prediction.png \"Title\")\n"
+ "<img src=\"./Bilder/imcap_prediction.png\" width=\"600\">\n"
]
},
{
@@ -5050,7 +5048,7 @@
}
],
"source": [
- "image = './Bilder/nachknast.jpg'\n",
+ "image = './Bilder/example_10.jpg'\n",
"result, attention_plot = evaluate(image)\n",
"print ('Prediction Caption:', ' '.join(result))\n",
"plot_attention(image, result, attention_plot)\n",
--
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