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Files changed (8) hide show
  1. app.ipynb +301 -0
  2. app.py +25 -4
  3. buffalo +0 -0
  4. cocacola +0 -0
  5. export.pkl +3 -0
  6. fanta +0 -0
  7. requirements.txt +2 -0
  8. sprite +0 -0
app.ipynb ADDED
@@ -0,0 +1,301 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ "cells": [
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+ {
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+ "cell_type": "code",
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+ "execution_count": 1,
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+ "id": "4efd5d86-880a-4d3c-83aa-261bc366f135",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "#|default_exp app"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 2,
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+ "id": "cbddd540-bb9a-447d-89d8-5592b6c9227c",
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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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+ "#|export\n",
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+ "from fastai.vision.all import *\n",
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+ "import gradio as gr\n",
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+ "\n"
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+ ]
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+ },
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+ {
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+ "cell_type": "code",
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+ "execution_count": 3,
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+ "id": "e1cc14ec-4439-4429-a329-5eef3fc90fe5",
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+ "metadata": {},
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+ "outputs": [
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+ {
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+ "data": {
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+ "image/png": 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\n",
35
+ "text/plain": [
36
+ "PILImage mode=RGB size=144x192"
37
+ ]
38
+ },
39
+ "execution_count": 3,
40
+ "metadata": {},
41
+ "output_type": "execute_result"
42
+ }
43
+ ],
44
+ "source": [
45
+ "im = PILImage.create('fanta')\n",
46
+ "im.thumbnail((192,192))\n",
47
+ "im"
48
+ ]
49
+ },
50
+ {
51
+ "cell_type": "code",
52
+ "execution_count": 4,
53
+ "id": "a6d79d0d-03a1-4b8f-bbcc-846f5c6712af",
54
+ "metadata": {},
55
+ "outputs": [],
56
+ "source": [
57
+ "#|export\n",
58
+ "learn = load_learner('export.pkl')"
59
+ ]
60
+ },
61
+ {
62
+ "cell_type": "code",
63
+ "execution_count": 5,
64
+ "id": "8b883750-11c0-418c-ba3c-cbe6a472232d",
65
+ "metadata": {},
66
+ "outputs": [
67
+ {
68
+ "data": {
69
+ "text/html": [
70
+ "\n",
71
+ "<style>\n",
72
+ " /* Turns off some styling */\n",
73
+ " progress {\n",
74
+ " /* gets rid of default border in Firefox and Opera. */\n",
75
+ " border: none;\n",
76
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
77
+ " background-size: auto;\n",
78
+ " }\n",
79
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
80
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
81
+ " }\n",
82
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
83
+ " background: #F44336;\n",
84
+ " }\n",
85
+ "</style>\n"
86
+ ],
87
+ "text/plain": [
88
+ "<IPython.core.display.HTML object>"
89
+ ]
90
+ },
91
+ "metadata": {},
92
+ "output_type": "display_data"
93
+ },
94
+ {
95
+ "data": {
96
+ "text/html": [],
97
+ "text/plain": [
98
+ "<IPython.core.display.HTML object>"
99
+ ]
100
+ },
101
+ "metadata": {},
102
+ "output_type": "display_data"
103
+ },
104
+ {
105
+ "data": {
106
+ "text/plain": [
107
+ "('fanta', TensorBase(1), TensorBase([1.7609e-04, 9.9982e-01, 6.8624e-06]))"
108
+ ]
109
+ },
110
+ "execution_count": 5,
111
+ "metadata": {},
112
+ "output_type": "execute_result"
113
+ }
114
+ ],
115
+ "source": [
116
+ "learn.predict(im)"
117
+ ]
118
+ },
119
+ {
120
+ "cell_type": "code",
121
+ "execution_count": 6,
122
+ "id": "9d8ddf37-4651-4913-a742-23bf5d02d468",
123
+ "metadata": {},
124
+ "outputs": [],
125
+ "source": [
126
+ "#|export\n",
127
+ "categories = ('cocacola', 'fanta', 'sprite')\n",
128
+ "\n",
129
+ "def classify_image(img):\n",
130
+ " pred,idx,probs = learn.predict(img)\n",
131
+ " return dict(zip(categories, map(float,probs)))"
132
+ ]
133
+ },
134
+ {
135
+ "cell_type": "code",
136
+ "execution_count": 7,
137
+ "id": "4f38e431-774f-4192-aa29-95c96ef7c3ab",
138
+ "metadata": {},
139
+ "outputs": [
140
+ {
141
+ "data": {
142
+ "text/html": [
143
+ "\n",
144
+ "<style>\n",
145
+ " /* Turns off some styling */\n",
146
+ " progress {\n",
147
+ " /* gets rid of default border in Firefox and Opera. */\n",
148
+ " border: none;\n",
149
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
150
+ " background-size: auto;\n",
151
+ " }\n",
152
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
153
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
154
+ " }\n",
155
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
156
+ " background: #F44336;\n",
157
+ " }\n",
158
+ "</style>\n"
159
+ ],
160
+ "text/plain": [
161
+ "<IPython.core.display.HTML object>"
162
+ ]
163
+ },
164
+ "metadata": {},
165
+ "output_type": "display_data"
166
+ },
167
+ {
168
+ "data": {
169
+ "text/html": [],
170
+ "text/plain": [
171
+ "<IPython.core.display.HTML object>"
172
+ ]
173
+ },
174
+ "metadata": {},
175
+ "output_type": "display_data"
176
+ },
177
+ {
178
+ "data": {
179
+ "text/plain": [
180
+ "{'cocacola': 0.00017608856433071196,\n",
181
+ " 'fanta': 0.9998170733451843,\n",
182
+ " 'sprite': 6.862403552077012e-06}"
183
+ ]
184
+ },
185
+ "execution_count": 7,
186
+ "metadata": {},
187
+ "output_type": "execute_result"
188
+ }
189
+ ],
190
+ "source": [
191
+ "classify_image(im)"
192
+ ]
193
+ },
194
+ {
195
+ "cell_type": "code",
196
+ "execution_count": 8,
197
+ "id": "cba39441-a384-42a6-9e3f-41eacb794d35",
198
+ "metadata": {},
199
+ "outputs": [
200
+ {
201
+ "name": "stderr",
202
+ "output_type": "stream",
203
+ "text": [
204
+ "/home/fcabello/git/minimal/venv/lib/python3.9/site-packages/gradio/inputs.py:256: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
205
+ " warnings.warn(\n",
206
+ "/home/fcabello/git/minimal/venv/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
207
+ " warnings.warn(value)\n",
208
+ "/home/fcabello/git/minimal/venv/lib/python3.9/site-packages/gradio/outputs.py:196: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
209
+ " warnings.warn(\n",
210
+ "/home/fcabello/git/minimal/venv/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
211
+ " warnings.warn(value)\n"
212
+ ]
213
+ },
214
+ {
215
+ "name": "stdout",
216
+ "output_type": "stream",
217
+ "text": [
218
+ "Running on local URL: http://127.0.0.1:7860\n",
219
+ "\n",
220
+ "To create a public link, set `share=True` in `launch()`.\n"
221
+ ]
222
+ },
223
+ {
224
+ "data": {
225
+ "text/plain": []
226
+ },
227
+ "execution_count": 8,
228
+ "metadata": {},
229
+ "output_type": "execute_result"
230
+ }
231
+ ],
232
+ "source": [
233
+ "#|export\n",
234
+ "\n",
235
+ "image = gr.inputs.Image(shape=(192, 192))\n",
236
+ "label = gr.outputs.Label()\n",
237
+ "examples = ['cocacola', 'fanta', 'sprite', 'buffalo']\n",
238
+ "\n",
239
+ "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
240
+ "intf.launch(inline=False)"
241
+ ]
242
+ },
243
+ {
244
+ "cell_type": "code",
245
+ "execution_count": 9,
246
+ "id": "4b6b9ec7-b5f5-40c9-86b9-3de8670fc3c5",
247
+ "metadata": {},
248
+ "outputs": [],
249
+ "source": [
250
+ "import nbdev.export as xprt"
251
+ ]
252
+ },
253
+ {
254
+ "cell_type": "code",
255
+ "execution_count": 10,
256
+ "id": "c2874b40-ba50-4c65-9cee-4eddd039297d",
257
+ "metadata": {},
258
+ "outputs": [],
259
+ "source": [
260
+ "xprt.nb_export('app.ipynb', 'app.py')"
261
+ ]
262
+ },
263
+ {
264
+ "cell_type": "code",
265
+ "execution_count": null,
266
+ "id": "956df7f6-7a6d-47d7-9c5d-369eee2de98b",
267
+ "metadata": {},
268
+ "outputs": [],
269
+ "source": []
270
+ },
271
+ {
272
+ "cell_type": "code",
273
+ "execution_count": null,
274
+ "id": "fdee54c8-a4d9-47e5-b962-81317808a397",
275
+ "metadata": {},
276
+ "outputs": [],
277
+ "source": []
278
+ }
279
+ ],
280
+ "metadata": {
281
+ "kernelspec": {
282
+ "display_name": "Python 3 (ipykernel)",
283
+ "language": "python",
284
+ "name": "python3"
285
+ },
286
+ "language_info": {
287
+ "codemirror_mode": {
288
+ "name": "ipython",
289
+ "version": 3
290
+ },
291
+ "file_extension": ".py",
292
+ "mimetype": "text/x-python",
293
+ "name": "python",
294
+ "nbconvert_exporter": "python",
295
+ "pygments_lexer": "ipython3",
296
+ "version": "3.9.10"
297
+ }
298
+ },
299
+ "nbformat": 4,
300
+ "nbformat_minor": 5
301
+ }
app.py CHANGED
@@ -1,7 +1,28 @@
 
 
 
 
 
 
 
1
  import gradio as gr
2
 
3
- def greet(name):
4
- return "Hello " + name + "!!"
5
 
6
- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
7
- iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ # AUTOGENERATED! DO NOT EDIT! File to edit: ../app.ipynb.
2
+
3
+ # %% auto 0
4
+ __all__ = ['learn', 'categories', 'image', 'label', 'examples', 'intf', 'classify_image']
5
+
6
+ # %% ../app.ipynb 1
7
+ from fastai.vision.all import *
8
  import gradio as gr
9
 
 
 
10
 
11
+
12
+ # %% ../app.ipynb 3
13
+ learn = load_learner('export.pkl')
14
+
15
+ # %% ../app.ipynb 5
16
+ categories = ('cocacola', 'fanta', 'sprite')
17
+
18
+ def classify_image(img):
19
+ pred,idx,probs = learn.predict(img)
20
+ return dict(zip(categories, map(float,probs)))
21
+
22
+ # %% ../app.ipynb 7
23
+ image = gr.inputs.Image(shape=(192, 192))
24
+ label = gr.outputs.Label()
25
+ examples = ['cocacola', 'fanta', 'sprite', 'buffalo']
26
+
27
+ intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
28
+ intf.launch(inline=False)
buffalo ADDED
Binary file (31 kB). View file
 
cocacola ADDED
Binary file (20.5 kB). View file
 
export.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:d74be7747fb1de1915ff2f41a64490df892735626749cdfcc5d63ad09f523c38
3
+ size 46964175
fanta ADDED
Binary file (509 kB). View file
 
requirements.txt ADDED
@@ -0,0 +1,2 @@
 
 
 
1
+ fastai
2
+ gradio
sprite ADDED
Binary file (14.5 kB). View file