ddg

Author: jph00

docs/_data/sidebars/home_sidebar.yml

@@ -9,32 +9,11 @@ entries:
     - output: web,pdf
       title: Overview
       url: /
-    output: web
-    title: Getting started
-  - folderitems:
-    - output: web,pdf
-      title: Colab
-      url: /start_colab
-    - output: web,pdf
-      title: Gradient
-      url: /start_gradient
-    - output: web,pdf
-      title: Sagemaker
-      url: /start_sagemaker
-    output: web
-    title: Notebook Servers
-  - folderitems:
-    - output: web,pdf
-      title: Google Cloud
-      url: /start_gcp
-    - output: web,pdf
-      title: Azure
-      url: /start_azure_dsvm
     - output: web,pdf
-      title: DataCrunch.io
-      url: /start_datacrunch
+      title: Downloading images
+      url: /images
     output: web
-    title: Full Linux Servers
+    title: Book and course help
   - folderitems:
     - output: web,pdf
       title: Lesson 1 - Your first models
@@ -62,13 +41,40 @@ entries:
       url: videos?lesson=8
     output: web
     title: Lessons
+  - folderitems:
+    - output: web,pdf
+      title: Colab
+      url: /start_colab
+    - output: web,pdf
+      title: Gradient
+      url: /start_gradient
+    - output: web,pdf
+      title: Sagemaker
+      url: /start_sagemaker
+    output: web
+    title: Notebook Servers
+  - folderitems:
+    - output: web,pdf
+      title: Google Cloud
+      url: /start_gcp
+    - output: web,pdf
+      title: Azure
+      url: /start_azure_dsvm
+    - output: web,pdf
+      title: DataCrunch.io
+      url: /start_datacrunch
+    output: web
+    title: Full Linux Servers
   - folderitems:
     - output: web,pdf
       title: Heroku
       url: /deployment_heroku
     - output: web,pdf
       title: Azure Functions
       url: /deployment_azure_functions
+    - output: web,pdf
+      title: BentoML
+      url: /deployment_bento
     - output: web,pdf
       title: SeeMe.ai
       url: /deployment_seeme_ai

docs/images.html

@@ -1,14 +1,7 @@
 {
-  "Getting started": {
-    "Overview": "/"
-  }, "Notebook Servers": {
-    "Colab": "/start_colab",
-    "Gradient": "/start_gradient",
-    "Sagemaker": "/start_sagemaker"
-  }, "Full Linux Servers": {
-      "Google Cloud": "/start_gcp",
-      "Azure": "/start_azure_dsvm",
-      "DataCrunch.io": "/start_datacrunch"
+  "Book and course help": {
+    "Overview": "/",
+    "Downloading images": "/images"
   }, "Lessons": {
     "Lesson 1 - Your first models": "videos?lesson=1",
     "Lesson 2 - Evidence and p values": "videos?lesson=2",
@@ -18,6 +11,14 @@
     "Lesson 6 - Collaborative filtering": "videos?lesson=6",
     "Lesson 7 - Tabular data": "videos?lesson=7",
     "Lesson 8 - Natural language processing": "videos?lesson=8"
+  }, "Notebook Servers": {
+    "Colab": "/start_colab",
+    "Gradient": "/start_gradient",
+    "Sagemaker": "/start_sagemaker"
+  }, "Full Linux Servers": {
+      "Google Cloud": "/start_gcp",
+      "Azure": "/start_azure_dsvm",
+      "DataCrunch.io": "/start_datacrunch"
   }, "Deployment": {
     "Heroku": "/deployment_heroku",
     "Azure Functions": "/deployment_azure_functions",

docs/images/bear.jpg

@@ -1,9 +1,10 @@
-__version__ = "0.0.15"
-import matplotlib as mpl, pkgutil, requests
+__version__ = "0.0.16"
+import matplotlib as mpl, pkgutil, requests, time
 from fastai.vision.all import *
 from pandas.api.types import CategoricalDtype
 from scipy.cluster import hierarchy as hc
 from io import StringIO, BytesIO
+from urllib.error import URLError,HTTPError
 
 try: from ipywidgets import widgets
 except ModuleNotFoundError: warn("Missing `ipywidgets` - please install it")
@@ -42,14 +43,31 @@ def gv(s): return graphviz.Source('digraph G{ rankdir="LR"' + s + '; }')
 def get_image_files_sorted(path, recurse=True, folders=None):
     return get_image_files(path, recurse, folders).sorted()
 
-def search_images_bing(key,earch_images_bing(key, term, min_sz=128, max_images=150):
-    params = {'q':term, 'count':max_images, 'min_height':min_sz, 'min_width':min_sz}
-    headers = {"Ocp-Apim-Subscription-Key":key}
+def search_images_bing(key, term, min_sz=128, max_images=150):
+    params = dict(q=term, count=max_images, min_height=min_sz, min_width=min_sz)
     search_url = "https://api.bing.microsoft.com/v7.0/images/search"
-    response = requests.get(search_url, headers=headers, params=params)
+    response = requests.get(search_url, headers={"Ocp-Apim-Subscription-Key":key}, params=params)
     response.raise_for_status()
-    search_results = response.json()
-    return L(search_results['value'])term, Min_sz=128):
+    return L(response.json()['value'])
+
+def search_images_ddg(term, max_images=200):
+    "Search for `term` with DuckDuckGo and return a unique urls of about `max_images` images"
+    assert max_images<1000
+    url = 'https://duckduckgo.com/'
+    res = urlread(url,data={'q':term}).decode()
+    searchObj = re.search(r'vqd=([\d-]+)\&', res)
+    assert searchObj
+    requestUrl = url + 'i.js'
+    params = dict(l='us-en', o='json', q=term, vqd=searchObj.group(1), f=',,,', p='1', v7exp='a')
+    urls,data = set(),{'next':1}
+    while len(urls)<max_images and 'next' in data:
+        try:
+            data = urljson(requestUrl,data=params)
+            urls.update(L(data['results']).itemgot('image'))
+            requestUrl = url + data['next']
+        except (URLError,HTTPError): pass
+        time.sleep(0.2)
+    return L(urls)
 
 def plot_function(f, tx=None, ty=None, title=None, min=-2, max=2, figsize=(6,4)):
     x = torch.linspace(min,max)

docs/sidebar.json

@@ -7,7 +7,7 @@ author = Jeremy Howard and Sylvain Gugger
 author_email = [email protected]
 copyright = fast.ai
 branch = master
-version = 0.0.15
+version = 0.0.16
 min_python = 3.6
 audience = Developers
 language = English