Mario Namtao Shianti Larcher commited on
Commit
5aaadde
1 Parent(s): 4884eb3

Update app

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Files changed (2) hide show
  1. app.ipynb +355 -0
  2. app.py +18 -5
app.ipynb ADDED
@@ -0,0 +1,355 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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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+ "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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+ "metadata": {},
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+ "outputs": [],
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+ "source": [
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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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+ "def is_cat(x): return x[0].isupper()"
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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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+ "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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",
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+ "text/plain": [
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+ "PILImage mode=RGB size=192x128"
34
+ ]
35
+ },
36
+ "execution_count": 3,
37
+ "metadata": {},
38
+ "output_type": "execute_result"
39
+ }
40
+ ],
41
+ "source": [
42
+ "im = PILImage.create(\"dog.jpg\")\n",
43
+ "im.thumbnail((192, 192))\n",
44
+ "im"
45
+ ]
46
+ },
47
+ {
48
+ "cell_type": "code",
49
+ "execution_count": 4,
50
+ "metadata": {},
51
+ "outputs": [],
52
+ "source": [
53
+ "#|export\n",
54
+ "learn = load_learner(\"model.pkl\")"
55
+ ]
56
+ },
57
+ {
58
+ "cell_type": "code",
59
+ "execution_count": 5,
60
+ "metadata": {},
61
+ "outputs": [
62
+ {
63
+ "data": {
64
+ "text/html": [
65
+ "\n",
66
+ "<style>\n",
67
+ " /* Turns off some styling */\n",
68
+ " progress {\n",
69
+ " /* gets rid of default border in Firefox and Opera. */\n",
70
+ " border: none;\n",
71
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
72
+ " background-size: auto;\n",
73
+ " }\n",
74
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
75
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
76
+ " }\n",
77
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
78
+ " background: #F44336;\n",
79
+ " }\n",
80
+ "</style>\n"
81
+ ],
82
+ "text/plain": [
83
+ "<IPython.core.display.HTML object>"
84
+ ]
85
+ },
86
+ "metadata": {},
87
+ "output_type": "display_data"
88
+ },
89
+ {
90
+ "data": {
91
+ "text/html": [],
92
+ "text/plain": [
93
+ "<IPython.core.display.HTML object>"
94
+ ]
95
+ },
96
+ "metadata": {},
97
+ "output_type": "display_data"
98
+ },
99
+ {
100
+ "name": "stderr",
101
+ "output_type": "stream",
102
+ "text": [
103
+ "[W NNPACK.cpp:53] Could not initialize NNPACK! Reason: Unsupported hardware.\n"
104
+ ]
105
+ },
106
+ {
107
+ "name": "stdout",
108
+ "output_type": "stream",
109
+ "text": [
110
+ "CPU times: user 323 ms, sys: 61.7 ms, total: 384 ms\n",
111
+ "Wall time: 429 ms\n"
112
+ ]
113
+ },
114
+ {
115
+ "data": {
116
+ "text/plain": [
117
+ "('False', TensorBase(0), TensorBase([1.0000e+00, 1.8276e-08]))"
118
+ ]
119
+ },
120
+ "execution_count": 5,
121
+ "metadata": {},
122
+ "output_type": "execute_result"
123
+ }
124
+ ],
125
+ "source": [
126
+ "%time learn.predict(im)"
127
+ ]
128
+ },
129
+ {
130
+ "cell_type": "code",
131
+ "execution_count": 6,
132
+ "metadata": {},
133
+ "outputs": [
134
+ {
135
+ "data": {
136
+ "text/html": [
137
+ "\n",
138
+ "<style>\n",
139
+ " /* Turns off some styling */\n",
140
+ " progress {\n",
141
+ " /* gets rid of default border in Firefox and Opera. */\n",
142
+ " border: none;\n",
143
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
144
+ " background-size: auto;\n",
145
+ " }\n",
146
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
147
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
148
+ " }\n",
149
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
150
+ " background: #F44336;\n",
151
+ " }\n",
152
+ "</style>\n"
153
+ ],
154
+ "text/plain": [
155
+ "<IPython.core.display.HTML object>"
156
+ ]
157
+ },
158
+ "metadata": {},
159
+ "output_type": "display_data"
160
+ },
161
+ {
162
+ "data": {
163
+ "text/html": [],
164
+ "text/plain": [
165
+ "<IPython.core.display.HTML object>"
166
+ ]
167
+ },
168
+ "metadata": {},
169
+ "output_type": "display_data"
170
+ },
171
+ {
172
+ "data": {
173
+ "text/plain": [
174
+ "('False', TensorBase(0), TensorBase([1.0000e+00, 1.8276e-08]))"
175
+ ]
176
+ },
177
+ "execution_count": 6,
178
+ "metadata": {},
179
+ "output_type": "execute_result"
180
+ }
181
+ ],
182
+ "source": [
183
+ "learn.predict(im)"
184
+ ]
185
+ },
186
+ {
187
+ "cell_type": "code",
188
+ "execution_count": 7,
189
+ "metadata": {},
190
+ "outputs": [],
191
+ "source": [
192
+ "#|export\n",
193
+ "categories = (\"Dog\", \"Cat\")\n",
194
+ "\n",
195
+ "def classify_image(img):\n",
196
+ " _, _, probs = learn.predict(img)\n",
197
+ " return dict(zip(categories, map(float, probs)))"
198
+ ]
199
+ },
200
+ {
201
+ "cell_type": "code",
202
+ "execution_count": 8,
203
+ "metadata": {},
204
+ "outputs": [
205
+ {
206
+ "data": {
207
+ "text/html": [
208
+ "\n",
209
+ "<style>\n",
210
+ " /* Turns off some styling */\n",
211
+ " progress {\n",
212
+ " /* gets rid of default border in Firefox and Opera. */\n",
213
+ " border: none;\n",
214
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
215
+ " background-size: auto;\n",
216
+ " }\n",
217
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
218
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
219
+ " }\n",
220
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
221
+ " background: #F44336;\n",
222
+ " }\n",
223
+ "</style>\n"
224
+ ],
225
+ "text/plain": [
226
+ "<IPython.core.display.HTML object>"
227
+ ]
228
+ },
229
+ "metadata": {},
230
+ "output_type": "display_data"
231
+ },
232
+ {
233
+ "data": {
234
+ "text/html": [],
235
+ "text/plain": [
236
+ "<IPython.core.display.HTML object>"
237
+ ]
238
+ },
239
+ "metadata": {},
240
+ "output_type": "display_data"
241
+ },
242
+ {
243
+ "data": {
244
+ "text/plain": [
245
+ "{'Dog': 1.0, 'Cat': 1.8276288926699635e-08}"
246
+ ]
247
+ },
248
+ "execution_count": 8,
249
+ "metadata": {},
250
+ "output_type": "execute_result"
251
+ }
252
+ ],
253
+ "source": [
254
+ "classify_image(im)"
255
+ ]
256
+ },
257
+ {
258
+ "cell_type": "code",
259
+ "execution_count": 9,
260
+ "metadata": {},
261
+ "outputs": [
262
+ {
263
+ "name": "stderr",
264
+ "output_type": "stream",
265
+ "text": [
266
+ "/Users/manuelalarcher/miniconda3/lib/python3.9/site-packages/gradio/inputs.py:257: UserWarning: Usage of gradio.inputs is deprecated, and will not be supported in the future, please import your component from gradio.components\n",
267
+ " warnings.warn(\n",
268
+ "/Users/manuelalarcher/miniconda3/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
269
+ " warnings.warn(value)\n",
270
+ "/Users/manuelalarcher/miniconda3/lib/python3.9/site-packages/gradio/outputs.py:197: UserWarning: Usage of gradio.outputs is deprecated, and will not be supported in the future, please import your components from gradio.components\n",
271
+ " warnings.warn(\n",
272
+ "/Users/manuelalarcher/miniconda3/lib/python3.9/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
273
+ " warnings.warn(value)\n"
274
+ ]
275
+ },
276
+ {
277
+ "name": "stdout",
278
+ "output_type": "stream",
279
+ "text": [
280
+ "Running on local URL: http://127.0.0.1:7860\n",
281
+ "\n",
282
+ "To create a public link, set `share=True` in `launch()`.\n"
283
+ ]
284
+ },
285
+ {
286
+ "data": {
287
+ "text/plain": []
288
+ },
289
+ "execution_count": 9,
290
+ "metadata": {},
291
+ "output_type": "execute_result"
292
+ }
293
+ ],
294
+ "source": [
295
+ "#|export\n",
296
+ "image = gr.inputs.Image(shape=(192, 192))\n",
297
+ "label = gr.outputs.Label()\n",
298
+ "examples = [\"dog.jpg\", \"cat.jpg\", \"dunno.jpg\"]\n",
299
+ "\n",
300
+ "intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
301
+ "intf.launch(inline=False)"
302
+ ]
303
+ },
304
+ {
305
+ "cell_type": "markdown",
306
+ "metadata": {},
307
+ "source": [
308
+ "### Export"
309
+ ]
310
+ },
311
+ {
312
+ "cell_type": "code",
313
+ "execution_count": 10,
314
+ "metadata": {},
315
+ "outputs": [],
316
+ "source": [
317
+ "from nbdev.export import nb_export"
318
+ ]
319
+ },
320
+ {
321
+ "cell_type": "code",
322
+ "execution_count": 11,
323
+ "metadata": {},
324
+ "outputs": [],
325
+ "source": [
326
+ "nb_export(\"app.ipynb\", \"./\")"
327
+ ]
328
+ }
329
+ ],
330
+ "metadata": {
331
+ "interpreter": {
332
+ "hash": "fa0e7c2aa790e70256f50a02b7bc765e1169b9577a41fc99d5b8b903f3504b99"
333
+ },
334
+ "kernelspec": {
335
+ "display_name": "Python 3.9.7 ('base')",
336
+ "language": "python",
337
+ "name": "python3"
338
+ },
339
+ "language_info": {
340
+ "codemirror_mode": {
341
+ "name": "ipython",
342
+ "version": 3
343
+ },
344
+ "file_extension": ".py",
345
+ "mimetype": "text/x-python",
346
+ "name": "python",
347
+ "nbconvert_exporter": "python",
348
+ "pygments_lexer": "ipython3",
349
+ "version": "3.9.7"
350
+ },
351
+ "orig_nbformat": 4
352
+ },
353
+ "nbformat": 4,
354
+ "nbformat_minor": 2
355
+ }
app.py CHANGED
@@ -1,9 +1,22 @@
1
- import gradio as gr
2
 
 
 
3
 
4
- def greet(name):
5
- return "Hello" + name + "!!"
6
 
 
 
7
 
8
- iface = gr.Interface(fn=greet, inputs="text", outputs="text")
9
- 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 3
7
+ learn = load_learner("model.pkl")
8
 
9
+ # %% app.ipynb 6
10
+ categories = ("Dog", "Cat")
11
 
12
+ def classify_image(img):
13
+ _, _, probs = learn.predict(img)
14
+ return dict(zip(categories, map(float, probs)))
15
+
16
+ # %% app.ipynb 8
17
+ image = gr.inputs.Image(shape=(192, 192))
18
+ label = gr.outputs.Label()
19
+ examples = ["dog.jpg", "cat.jpg", "dunno.jpg"]
20
+
21
+ intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
22
+ intf.launch(inline=False)