feat: Add cat classifier app
Browse files
app.py
CHANGED
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import gradio as gr
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def
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iface = gr.Interface(fn=greet, inputs="text", outputs="text")
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iface.launch()
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# AUTOGENERATED! DO NOT EDIT! File to edit: ../test_hugging_face.ipynb.
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# %% auto 0
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__all__ = ['learn', 'categories', 'image', 'label', 'examples', 'iface', 'is_cat', 'classify_image']
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# %% ../test_hugging_face.ipynb 2
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from fastai.vision.all import *
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import gradio as gr
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def is_cat(): return x[0].isupper()
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# %% ../test_hugging_face.ipynb 4
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learn = load_learner('model.pkl')
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# %% ../test_hugging_face.ipynb 6
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categories = ('Dog', 'Cat')
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def classify_image(img):
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pred, id, prob = learn.predict(img)
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return dict(zip(categories, map(float, prob)))
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# %% ../test_hugging_face.ipynb 8
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image = gr.components.Image(width=192, height=192)
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label = gr.components.Label()
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examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']
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iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
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iface.launch(inline=False)
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cat.jpg
ADDED
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dog.jpg
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dunno.jpg
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model.pkl
ADDED
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version https://git-lfs.github.com/spec/v1
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oid sha256:080428815e5438f820e344f4cb56ac2eec871d2a52a6b839f1d4d8c04b4c6e27
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size 47061419
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test_hugging_face.ipynb
ADDED
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@@ -0,0 +1,635 @@
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{
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| 2 |
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"cells": [
|
| 3 |
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{
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| 4 |
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"cell_type": "code",
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| 5 |
+
"execution_count": 14,
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| 6 |
+
"id": "6a93906c-400a-4747-82a6-728846c58ab7",
|
| 7 |
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"metadata": {},
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| 8 |
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"outputs": [],
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| 9 |
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"source": [
|
| 10 |
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"# Make sure we've got the latest version of fastai:\n",
|
| 11 |
+
"# !pip install -Uqq fastai gradio nbdev"
|
| 12 |
+
]
|
| 13 |
+
},
|
| 14 |
+
{
|
| 15 |
+
"cell_type": "code",
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| 16 |
+
"execution_count": 2,
|
| 17 |
+
"id": "2aff42ca-eaec-4e00-8688-80937837bcd9",
|
| 18 |
+
"metadata": {},
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| 19 |
+
"outputs": [],
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| 20 |
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"source": [
|
| 21 |
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"#|default_exp app"
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| 22 |
+
]
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| 23 |
+
},
|
| 24 |
+
{
|
| 25 |
+
"cell_type": "code",
|
| 26 |
+
"execution_count": 3,
|
| 27 |
+
"id": "67c90cb4-c402-440b-84f4-6155652a4fa9",
|
| 28 |
+
"metadata": {},
|
| 29 |
+
"outputs": [
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| 30 |
+
{
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| 31 |
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"name": "stderr",
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| 32 |
+
"output_type": "stream",
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| 33 |
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"text": [
|
| 34 |
+
"/Users/pqrsjk/venv-for-jupyter/lib/python3.9/site-packages/urllib3/__init__.py:35: NotOpenSSLWarning: urllib3 v2 only supports OpenSSL 1.1.1+, currently the 'ssl' module is compiled with 'LibreSSL 2.8.3'. See: https://github.com/urllib3/urllib3/issues/3020\n",
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| 35 |
+
" warnings.warn(\n"
|
| 36 |
+
]
|
| 37 |
+
}
|
| 38 |
+
],
|
| 39 |
+
"source": [
|
| 40 |
+
"#|export\n",
|
| 41 |
+
"from fastai.vision.all import *\n",
|
| 42 |
+
"import gradio as gr\n",
|
| 43 |
+
"\n",
|
| 44 |
+
"def is_cat(): return x[0].isupper()"
|
| 45 |
+
]
|
| 46 |
+
},
|
| 47 |
+
{
|
| 48 |
+
"cell_type": "code",
|
| 49 |
+
"execution_count": 4,
|
| 50 |
+
"id": "24e5f14b-f2f7-4852-ae87-83259aadfc55",
|
| 51 |
+
"metadata": {},
|
| 52 |
+
"outputs": [
|
| 53 |
+
{
|
| 54 |
+
"data": {
|
| 55 |
+
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",
|
| 57 |
+
"text/plain": [
|
| 58 |
+
"PILImage mode=RGB size=192x128"
|
| 59 |
+
]
|
| 60 |
+
},
|
| 61 |
+
"execution_count": 4,
|
| 62 |
+
"metadata": {},
|
| 63 |
+
"output_type": "execute_result"
|
| 64 |
+
}
|
| 65 |
+
],
|
| 66 |
+
"source": [
|
| 67 |
+
"im = PILImage.create('dog.jpg')\n",
|
| 68 |
+
"im.thumbnail((192, 192))\n",
|
| 69 |
+
"im"
|
| 70 |
+
]
|
| 71 |
+
},
|
| 72 |
+
{
|
| 73 |
+
"cell_type": "code",
|
| 74 |
+
"execution_count": 5,
|
| 75 |
+
"id": "d0e8ae51-04f1-427a-b0ab-0bd05c37a88d",
|
| 76 |
+
"metadata": {},
|
| 77 |
+
"outputs": [],
|
| 78 |
+
"source": [
|
| 79 |
+
"#|export\n",
|
| 80 |
+
"learn = load_learner('model.pkl')"
|
| 81 |
+
]
|
| 82 |
+
},
|
| 83 |
+
{
|
| 84 |
+
"cell_type": "code",
|
| 85 |
+
"execution_count": 6,
|
| 86 |
+
"id": "4307f94e-e4cd-49ff-86fd-f364e421146b",
|
| 87 |
+
"metadata": {},
|
| 88 |
+
"outputs": [
|
| 89 |
+
{
|
| 90 |
+
"data": {
|
| 91 |
+
"text/html": [
|
| 92 |
+
"\n",
|
| 93 |
+
"<style>\n",
|
| 94 |
+
" /* Turns off some styling */\n",
|
| 95 |
+
" progress {\n",
|
| 96 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 97 |
+
" border: none;\n",
|
| 98 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 99 |
+
" background-size: auto;\n",
|
| 100 |
+
" }\n",
|
| 101 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 102 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 103 |
+
" }\n",
|
| 104 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 105 |
+
" background: #F44336;\n",
|
| 106 |
+
" }\n",
|
| 107 |
+
"</style>\n"
|
| 108 |
+
],
|
| 109 |
+
"text/plain": [
|
| 110 |
+
"<IPython.core.display.HTML object>"
|
| 111 |
+
]
|
| 112 |
+
},
|
| 113 |
+
"metadata": {},
|
| 114 |
+
"output_type": "display_data"
|
| 115 |
+
},
|
| 116 |
+
{
|
| 117 |
+
"data": {
|
| 118 |
+
"text/html": [],
|
| 119 |
+
"text/plain": [
|
| 120 |
+
"<IPython.core.display.HTML object>"
|
| 121 |
+
]
|
| 122 |
+
},
|
| 123 |
+
"metadata": {},
|
| 124 |
+
"output_type": "display_data"
|
| 125 |
+
},
|
| 126 |
+
{
|
| 127 |
+
"data": {
|
| 128 |
+
"text/plain": [
|
| 129 |
+
"('False', tensor(0), tensor([9.9999e-01, 6.6963e-06]))"
|
| 130 |
+
]
|
| 131 |
+
},
|
| 132 |
+
"execution_count": 6,
|
| 133 |
+
"metadata": {},
|
| 134 |
+
"output_type": "execute_result"
|
| 135 |
+
}
|
| 136 |
+
],
|
| 137 |
+
"source": [
|
| 138 |
+
"# %time learn.predict(im)\n",
|
| 139 |
+
"learn.predict(im)"
|
| 140 |
+
]
|
| 141 |
+
},
|
| 142 |
+
{
|
| 143 |
+
"cell_type": "code",
|
| 144 |
+
"execution_count": 7,
|
| 145 |
+
"id": "42365ae7-e5d1-462c-8d97-8e3305901c57",
|
| 146 |
+
"metadata": {},
|
| 147 |
+
"outputs": [],
|
| 148 |
+
"source": [
|
| 149 |
+
"#|export\n",
|
| 150 |
+
"categories = ('Dog', 'Cat')\n",
|
| 151 |
+
"\n",
|
| 152 |
+
"def classify_image(img):\n",
|
| 153 |
+
" pred, id, prob = learn.predict(img)\n",
|
| 154 |
+
" return dict(zip(categories, map(float, prob)))"
|
| 155 |
+
]
|
| 156 |
+
},
|
| 157 |
+
{
|
| 158 |
+
"cell_type": "code",
|
| 159 |
+
"execution_count": 8,
|
| 160 |
+
"id": "592d9011-9ccb-4a3c-9160-7d80bcc7c681",
|
| 161 |
+
"metadata": {},
|
| 162 |
+
"outputs": [
|
| 163 |
+
{
|
| 164 |
+
"data": {
|
| 165 |
+
"text/html": [
|
| 166 |
+
"\n",
|
| 167 |
+
"<style>\n",
|
| 168 |
+
" /* Turns off some styling */\n",
|
| 169 |
+
" progress {\n",
|
| 170 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 171 |
+
" border: none;\n",
|
| 172 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 173 |
+
" background-size: auto;\n",
|
| 174 |
+
" }\n",
|
| 175 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 176 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 177 |
+
" }\n",
|
| 178 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 179 |
+
" background: #F44336;\n",
|
| 180 |
+
" }\n",
|
| 181 |
+
"</style>\n"
|
| 182 |
+
],
|
| 183 |
+
"text/plain": [
|
| 184 |
+
"<IPython.core.display.HTML object>"
|
| 185 |
+
]
|
| 186 |
+
},
|
| 187 |
+
"metadata": {},
|
| 188 |
+
"output_type": "display_data"
|
| 189 |
+
},
|
| 190 |
+
{
|
| 191 |
+
"data": {
|
| 192 |
+
"text/html": [],
|
| 193 |
+
"text/plain": [
|
| 194 |
+
"<IPython.core.display.HTML object>"
|
| 195 |
+
]
|
| 196 |
+
},
|
| 197 |
+
"metadata": {},
|
| 198 |
+
"output_type": "display_data"
|
| 199 |
+
},
|
| 200 |
+
{
|
| 201 |
+
"data": {
|
| 202 |
+
"text/plain": [
|
| 203 |
+
"{'Dog': 0.9999933242797852, 'Cat': 6.696266609651502e-06}"
|
| 204 |
+
]
|
| 205 |
+
},
|
| 206 |
+
"execution_count": 8,
|
| 207 |
+
"metadata": {},
|
| 208 |
+
"output_type": "execute_result"
|
| 209 |
+
}
|
| 210 |
+
],
|
| 211 |
+
"source": [
|
| 212 |
+
"classify_image(im)"
|
| 213 |
+
]
|
| 214 |
+
},
|
| 215 |
+
{
|
| 216 |
+
"cell_type": "code",
|
| 217 |
+
"execution_count": 12,
|
| 218 |
+
"id": "e9715892-f73d-4774-ab75-8f1851d93d0a",
|
| 219 |
+
"metadata": {
|
| 220 |
+
"scrolled": true
|
| 221 |
+
},
|
| 222 |
+
"outputs": [
|
| 223 |
+
{
|
| 224 |
+
"name": "stdout",
|
| 225 |
+
"output_type": "stream",
|
| 226 |
+
"text": [
|
| 227 |
+
"Running on local URL: http://127.0.0.1:7860\n",
|
| 228 |
+
"\n",
|
| 229 |
+
"To create a public link, set `share=True` in `launch()`.\n"
|
| 230 |
+
]
|
| 231 |
+
},
|
| 232 |
+
{
|
| 233 |
+
"data": {
|
| 234 |
+
"text/plain": []
|
| 235 |
+
},
|
| 236 |
+
"execution_count": 12,
|
| 237 |
+
"metadata": {},
|
| 238 |
+
"output_type": "execute_result"
|
| 239 |
+
},
|
| 240 |
+
{
|
| 241 |
+
"data": {
|
| 242 |
+
"text/html": [
|
| 243 |
+
"\n",
|
| 244 |
+
"<style>\n",
|
| 245 |
+
" /* Turns off some styling */\n",
|
| 246 |
+
" progress {\n",
|
| 247 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 248 |
+
" border: none;\n",
|
| 249 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 250 |
+
" background-size: auto;\n",
|
| 251 |
+
" }\n",
|
| 252 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 253 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 254 |
+
" }\n",
|
| 255 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 256 |
+
" background: #F44336;\n",
|
| 257 |
+
" }\n",
|
| 258 |
+
"</style>\n"
|
| 259 |
+
],
|
| 260 |
+
"text/plain": [
|
| 261 |
+
"<IPython.core.display.HTML object>"
|
| 262 |
+
]
|
| 263 |
+
},
|
| 264 |
+
"metadata": {},
|
| 265 |
+
"output_type": "display_data"
|
| 266 |
+
},
|
| 267 |
+
{
|
| 268 |
+
"data": {
|
| 269 |
+
"text/html": [],
|
| 270 |
+
"text/plain": [
|
| 271 |
+
"<IPython.core.display.HTML object>"
|
| 272 |
+
]
|
| 273 |
+
},
|
| 274 |
+
"metadata": {},
|
| 275 |
+
"output_type": "display_data"
|
| 276 |
+
},
|
| 277 |
+
{
|
| 278 |
+
"data": {
|
| 279 |
+
"text/html": [
|
| 280 |
+
"\n",
|
| 281 |
+
"<style>\n",
|
| 282 |
+
" /* Turns off some styling */\n",
|
| 283 |
+
" progress {\n",
|
| 284 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 285 |
+
" border: none;\n",
|
| 286 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 287 |
+
" background-size: auto;\n",
|
| 288 |
+
" }\n",
|
| 289 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 290 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 291 |
+
" }\n",
|
| 292 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 293 |
+
" background: #F44336;\n",
|
| 294 |
+
" }\n",
|
| 295 |
+
"</style>\n"
|
| 296 |
+
],
|
| 297 |
+
"text/plain": [
|
| 298 |
+
"<IPython.core.display.HTML object>"
|
| 299 |
+
]
|
| 300 |
+
},
|
| 301 |
+
"metadata": {},
|
| 302 |
+
"output_type": "display_data"
|
| 303 |
+
},
|
| 304 |
+
{
|
| 305 |
+
"data": {
|
| 306 |
+
"text/html": [],
|
| 307 |
+
"text/plain": [
|
| 308 |
+
"<IPython.core.display.HTML object>"
|
| 309 |
+
]
|
| 310 |
+
},
|
| 311 |
+
"metadata": {},
|
| 312 |
+
"output_type": "display_data"
|
| 313 |
+
},
|
| 314 |
+
{
|
| 315 |
+
"data": {
|
| 316 |
+
"text/html": [
|
| 317 |
+
"\n",
|
| 318 |
+
"<style>\n",
|
| 319 |
+
" /* Turns off some styling */\n",
|
| 320 |
+
" progress {\n",
|
| 321 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 322 |
+
" border: none;\n",
|
| 323 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 324 |
+
" background-size: auto;\n",
|
| 325 |
+
" }\n",
|
| 326 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 327 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 328 |
+
" }\n",
|
| 329 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 330 |
+
" background: #F44336;\n",
|
| 331 |
+
" }\n",
|
| 332 |
+
"</style>\n"
|
| 333 |
+
],
|
| 334 |
+
"text/plain": [
|
| 335 |
+
"<IPython.core.display.HTML object>"
|
| 336 |
+
]
|
| 337 |
+
},
|
| 338 |
+
"metadata": {},
|
| 339 |
+
"output_type": "display_data"
|
| 340 |
+
},
|
| 341 |
+
{
|
| 342 |
+
"data": {
|
| 343 |
+
"text/html": [],
|
| 344 |
+
"text/plain": [
|
| 345 |
+
"<IPython.core.display.HTML object>"
|
| 346 |
+
]
|
| 347 |
+
},
|
| 348 |
+
"metadata": {},
|
| 349 |
+
"output_type": "display_data"
|
| 350 |
+
},
|
| 351 |
+
{
|
| 352 |
+
"data": {
|
| 353 |
+
"text/html": [
|
| 354 |
+
"\n",
|
| 355 |
+
"<style>\n",
|
| 356 |
+
" /* Turns off some styling */\n",
|
| 357 |
+
" progress {\n",
|
| 358 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 359 |
+
" border: none;\n",
|
| 360 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 361 |
+
" background-size: auto;\n",
|
| 362 |
+
" }\n",
|
| 363 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 364 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 365 |
+
" }\n",
|
| 366 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 367 |
+
" background: #F44336;\n",
|
| 368 |
+
" }\n",
|
| 369 |
+
"</style>\n"
|
| 370 |
+
],
|
| 371 |
+
"text/plain": [
|
| 372 |
+
"<IPython.core.display.HTML object>"
|
| 373 |
+
]
|
| 374 |
+
},
|
| 375 |
+
"metadata": {},
|
| 376 |
+
"output_type": "display_data"
|
| 377 |
+
},
|
| 378 |
+
{
|
| 379 |
+
"data": {
|
| 380 |
+
"text/html": [],
|
| 381 |
+
"text/plain": [
|
| 382 |
+
"<IPython.core.display.HTML object>"
|
| 383 |
+
]
|
| 384 |
+
},
|
| 385 |
+
"metadata": {},
|
| 386 |
+
"output_type": "display_data"
|
| 387 |
+
},
|
| 388 |
+
{
|
| 389 |
+
"data": {
|
| 390 |
+
"text/html": [
|
| 391 |
+
"\n",
|
| 392 |
+
"<style>\n",
|
| 393 |
+
" /* Turns off some styling */\n",
|
| 394 |
+
" progress {\n",
|
| 395 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 396 |
+
" border: none;\n",
|
| 397 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 398 |
+
" background-size: auto;\n",
|
| 399 |
+
" }\n",
|
| 400 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 401 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 402 |
+
" }\n",
|
| 403 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 404 |
+
" background: #F44336;\n",
|
| 405 |
+
" }\n",
|
| 406 |
+
"</style>\n"
|
| 407 |
+
],
|
| 408 |
+
"text/plain": [
|
| 409 |
+
"<IPython.core.display.HTML object>"
|
| 410 |
+
]
|
| 411 |
+
},
|
| 412 |
+
"metadata": {},
|
| 413 |
+
"output_type": "display_data"
|
| 414 |
+
},
|
| 415 |
+
{
|
| 416 |
+
"data": {
|
| 417 |
+
"text/html": [],
|
| 418 |
+
"text/plain": [
|
| 419 |
+
"<IPython.core.display.HTML object>"
|
| 420 |
+
]
|
| 421 |
+
},
|
| 422 |
+
"metadata": {},
|
| 423 |
+
"output_type": "display_data"
|
| 424 |
+
},
|
| 425 |
+
{
|
| 426 |
+
"data": {
|
| 427 |
+
"text/html": [
|
| 428 |
+
"\n",
|
| 429 |
+
"<style>\n",
|
| 430 |
+
" /* Turns off some styling */\n",
|
| 431 |
+
" progress {\n",
|
| 432 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 433 |
+
" border: none;\n",
|
| 434 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 435 |
+
" background-size: auto;\n",
|
| 436 |
+
" }\n",
|
| 437 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 438 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 439 |
+
" }\n",
|
| 440 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 441 |
+
" background: #F44336;\n",
|
| 442 |
+
" }\n",
|
| 443 |
+
"</style>\n"
|
| 444 |
+
],
|
| 445 |
+
"text/plain": [
|
| 446 |
+
"<IPython.core.display.HTML object>"
|
| 447 |
+
]
|
| 448 |
+
},
|
| 449 |
+
"metadata": {},
|
| 450 |
+
"output_type": "display_data"
|
| 451 |
+
},
|
| 452 |
+
{
|
| 453 |
+
"data": {
|
| 454 |
+
"text/html": [],
|
| 455 |
+
"text/plain": [
|
| 456 |
+
"<IPython.core.display.HTML object>"
|
| 457 |
+
]
|
| 458 |
+
},
|
| 459 |
+
"metadata": {},
|
| 460 |
+
"output_type": "display_data"
|
| 461 |
+
},
|
| 462 |
+
{
|
| 463 |
+
"data": {
|
| 464 |
+
"text/html": [
|
| 465 |
+
"\n",
|
| 466 |
+
"<style>\n",
|
| 467 |
+
" /* Turns off some styling */\n",
|
| 468 |
+
" progress {\n",
|
| 469 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 470 |
+
" border: none;\n",
|
| 471 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 472 |
+
" background-size: auto;\n",
|
| 473 |
+
" }\n",
|
| 474 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 475 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 476 |
+
" }\n",
|
| 477 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 478 |
+
" background: #F44336;\n",
|
| 479 |
+
" }\n",
|
| 480 |
+
"</style>\n"
|
| 481 |
+
],
|
| 482 |
+
"text/plain": [
|
| 483 |
+
"<IPython.core.display.HTML object>"
|
| 484 |
+
]
|
| 485 |
+
},
|
| 486 |
+
"metadata": {},
|
| 487 |
+
"output_type": "display_data"
|
| 488 |
+
},
|
| 489 |
+
{
|
| 490 |
+
"data": {
|
| 491 |
+
"text/html": [],
|
| 492 |
+
"text/plain": [
|
| 493 |
+
"<IPython.core.display.HTML object>"
|
| 494 |
+
]
|
| 495 |
+
},
|
| 496 |
+
"metadata": {},
|
| 497 |
+
"output_type": "display_data"
|
| 498 |
+
},
|
| 499 |
+
{
|
| 500 |
+
"data": {
|
| 501 |
+
"text/html": [
|
| 502 |
+
"\n",
|
| 503 |
+
"<style>\n",
|
| 504 |
+
" /* Turns off some styling */\n",
|
| 505 |
+
" progress {\n",
|
| 506 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 507 |
+
" border: none;\n",
|
| 508 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 509 |
+
" background-size: auto;\n",
|
| 510 |
+
" }\n",
|
| 511 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 512 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 513 |
+
" }\n",
|
| 514 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 515 |
+
" background: #F44336;\n",
|
| 516 |
+
" }\n",
|
| 517 |
+
"</style>\n"
|
| 518 |
+
],
|
| 519 |
+
"text/plain": [
|
| 520 |
+
"<IPython.core.display.HTML object>"
|
| 521 |
+
]
|
| 522 |
+
},
|
| 523 |
+
"metadata": {},
|
| 524 |
+
"output_type": "display_data"
|
| 525 |
+
},
|
| 526 |
+
{
|
| 527 |
+
"data": {
|
| 528 |
+
"text/html": [],
|
| 529 |
+
"text/plain": [
|
| 530 |
+
"<IPython.core.display.HTML object>"
|
| 531 |
+
]
|
| 532 |
+
},
|
| 533 |
+
"metadata": {},
|
| 534 |
+
"output_type": "display_data"
|
| 535 |
+
},
|
| 536 |
+
{
|
| 537 |
+
"data": {
|
| 538 |
+
"text/html": [
|
| 539 |
+
"\n",
|
| 540 |
+
"<style>\n",
|
| 541 |
+
" /* Turns off some styling */\n",
|
| 542 |
+
" progress {\n",
|
| 543 |
+
" /* gets rid of default border in Firefox and Opera. */\n",
|
| 544 |
+
" border: none;\n",
|
| 545 |
+
" /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
|
| 546 |
+
" background-size: auto;\n",
|
| 547 |
+
" }\n",
|
| 548 |
+
" progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
|
| 549 |
+
" background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
|
| 550 |
+
" }\n",
|
| 551 |
+
" .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
|
| 552 |
+
" background: #F44336;\n",
|
| 553 |
+
" }\n",
|
| 554 |
+
"</style>\n"
|
| 555 |
+
],
|
| 556 |
+
"text/plain": [
|
| 557 |
+
"<IPython.core.display.HTML object>"
|
| 558 |
+
]
|
| 559 |
+
},
|
| 560 |
+
"metadata": {},
|
| 561 |
+
"output_type": "display_data"
|
| 562 |
+
},
|
| 563 |
+
{
|
| 564 |
+
"data": {
|
| 565 |
+
"text/html": [],
|
| 566 |
+
"text/plain": [
|
| 567 |
+
"<IPython.core.display.HTML object>"
|
| 568 |
+
]
|
| 569 |
+
},
|
| 570 |
+
"metadata": {},
|
| 571 |
+
"output_type": "display_data"
|
| 572 |
+
}
|
| 573 |
+
],
|
| 574 |
+
"source": [
|
| 575 |
+
"#|export\n",
|
| 576 |
+
"image = gr.components.Image(width=192, height=192)\n",
|
| 577 |
+
"label = gr.components.Label()\n",
|
| 578 |
+
"examples = ['dog.jpg', 'cat.jpg', 'dunno.jpg']\n",
|
| 579 |
+
"\n",
|
| 580 |
+
"iface = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)\n",
|
| 581 |
+
"iface.launch(inline=False)\n"
|
| 582 |
+
]
|
| 583 |
+
},
|
| 584 |
+
{
|
| 585 |
+
"cell_type": "code",
|
| 586 |
+
"execution_count": 16,
|
| 587 |
+
"id": "ee2422bb-ccb3-492b-b704-aefe86f744ce",
|
| 588 |
+
"metadata": {},
|
| 589 |
+
"outputs": [],
|
| 590 |
+
"source": [
|
| 591 |
+
"import nbdev"
|
| 592 |
+
]
|
| 593 |
+
},
|
| 594 |
+
{
|
| 595 |
+
"cell_type": "code",
|
| 596 |
+
"execution_count": 18,
|
| 597 |
+
"id": "076f1d29-46f9-45c8-b71e-ed2f68635e67",
|
| 598 |
+
"metadata": {},
|
| 599 |
+
"outputs": [
|
| 600 |
+
{
|
| 601 |
+
"name": "stdout",
|
| 602 |
+
"output_type": "stream",
|
| 603 |
+
"text": [
|
| 604 |
+
"Export successful\n"
|
| 605 |
+
]
|
| 606 |
+
}
|
| 607 |
+
],
|
| 608 |
+
"source": [
|
| 609 |
+
"nbdev.export.nb_export('test_hugging_face.ipynb', 'app')\n",
|
| 610 |
+
"print('Export successful')"
|
| 611 |
+
]
|
| 612 |
+
}
|
| 613 |
+
],
|
| 614 |
+
"metadata": {
|
| 615 |
+
"kernelspec": {
|
| 616 |
+
"display_name": "Python 3 (ipykernel)",
|
| 617 |
+
"language": "python",
|
| 618 |
+
"name": "python3"
|
| 619 |
+
},
|
| 620 |
+
"language_info": {
|
| 621 |
+
"codemirror_mode": {
|
| 622 |
+
"name": "ipython",
|
| 623 |
+
"version": 3
|
| 624 |
+
},
|
| 625 |
+
"file_extension": ".py",
|
| 626 |
+
"mimetype": "text/x-python",
|
| 627 |
+
"name": "python",
|
| 628 |
+
"nbconvert_exporter": "python",
|
| 629 |
+
"pygments_lexer": "ipython3",
|
| 630 |
+
"version": "3.9.6"
|
| 631 |
+
}
|
| 632 |
+
},
|
| 633 |
+
"nbformat": 4,
|
| 634 |
+
"nbformat_minor": 5
|
| 635 |
+
}
|