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  1. app.ipynb +322 -0
  2. app.py +28 -0
  3. arcus.jpg +0 -0
  4. c.jpg +0 -0
  5. conjuc.jpg +0 -0
  6. eyec.jpeg +0 -0
  7. model.pkl +3 -0
  8. model.pkl:Zone.Identifier +3 -0
  9. nik.jpg +0 -0
app.ipynb ADDED
@@ -0,0 +1,322 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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": "a896f649",
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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": "81a0897e",
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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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+ ]
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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": "d9c851aa",
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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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",
34
+ "text/plain": [
35
+ "PILImage mode=RGB size=192x160"
36
+ ]
37
+ },
38
+ "execution_count": 3,
39
+ "metadata": {},
40
+ "output_type": "execute_result"
41
+ }
42
+ ],
43
+ "source": [
44
+ "im = PILImage.create('conjuc.jpg')\n",
45
+ "im.thumbnail((192,192))\n",
46
+ "im"
47
+ ]
48
+ },
49
+ {
50
+ "cell_type": "code",
51
+ "execution_count": 4,
52
+ "id": "055bc5ca",
53
+ "metadata": {},
54
+ "outputs": [],
55
+ "source": [
56
+ "#|export \n",
57
+ "learn = load_learner('model.pkl')"
58
+ ]
59
+ },
60
+ {
61
+ "cell_type": "code",
62
+ "execution_count": 5,
63
+ "id": "91d61ca8",
64
+ "metadata": {},
65
+ "outputs": [
66
+ {
67
+ "data": {
68
+ "text/html": [
69
+ "\n",
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+ "<style>\n",
71
+ " /* Turns off some styling */\n",
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+ " progress {\n",
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+ " /* gets rid of default border in Firefox and Opera. */\n",
74
+ " border: none;\n",
75
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
76
+ " background-size: auto;\n",
77
+ " }\n",
78
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
79
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
80
+ " }\n",
81
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
82
+ " background: #F44336;\n",
83
+ " }\n",
84
+ "</style>\n"
85
+ ],
86
+ "text/plain": [
87
+ "<IPython.core.display.HTML object>"
88
+ ]
89
+ },
90
+ "metadata": {},
91
+ "output_type": "display_data"
92
+ },
93
+ {
94
+ "data": {
95
+ "text/html": [],
96
+ "text/plain": [
97
+ "<IPython.core.display.HTML object>"
98
+ ]
99
+ },
100
+ "metadata": {},
101
+ "output_type": "display_data"
102
+ },
103
+ {
104
+ "data": {
105
+ "text/plain": [
106
+ "('conjuctivities',\n",
107
+ " tensor(2),\n",
108
+ " tensor([3.8550e-04, 5.8755e-04, 9.9421e-01, 2.2828e-03, 2.5374e-03]))"
109
+ ]
110
+ },
111
+ "execution_count": 5,
112
+ "metadata": {},
113
+ "output_type": "execute_result"
114
+ }
115
+ ],
116
+ "source": [
117
+ "learn.predict(im)"
118
+ ]
119
+ },
120
+ {
121
+ "cell_type": "code",
122
+ "execution_count": 6,
123
+ "id": "2e651440",
124
+ "metadata": {},
125
+ "outputs": [],
126
+ "source": [
127
+ "# Arcus, cataract , conjuctivities, eye cancer"
128
+ ]
129
+ },
130
+ {
131
+ "cell_type": "code",
132
+ "execution_count": 7,
133
+ "id": "72cac805",
134
+ "metadata": {},
135
+ "outputs": [],
136
+ "source": [
137
+ "#|export\n",
138
+ "categories = ('Arcus','Cataract','Conjuctivities','Eye Melanoma(Eye Cancer)','Normal Eye')\n",
139
+ "\n",
140
+ "def classify_image(img):\n",
141
+ " pred,idx,probs = learn.predict(img)\n",
142
+ " return dict(zip(categories,map(float,probs)))\n"
143
+ ]
144
+ },
145
+ {
146
+ "cell_type": "code",
147
+ "execution_count": 8,
148
+ "id": "6c29408a",
149
+ "metadata": {},
150
+ "outputs": [
151
+ {
152
+ "data": {
153
+ "text/html": [
154
+ "\n",
155
+ "<style>\n",
156
+ " /* Turns off some styling */\n",
157
+ " progress {\n",
158
+ " /* gets rid of default border in Firefox and Opera. */\n",
159
+ " border: none;\n",
160
+ " /* Needs to be in here for Safari polyfill so background images work as expected. */\n",
161
+ " background-size: auto;\n",
162
+ " }\n",
163
+ " progress:not([value]), progress:not([value])::-webkit-progress-bar {\n",
164
+ " background: repeating-linear-gradient(45deg, #7e7e7e, #7e7e7e 10px, #5c5c5c 10px, #5c5c5c 20px);\n",
165
+ " }\n",
166
+ " .progress-bar-interrupted, .progress-bar-interrupted::-webkit-progress-bar {\n",
167
+ " background: #F44336;\n",
168
+ " }\n",
169
+ "</style>\n"
170
+ ],
171
+ "text/plain": [
172
+ "<IPython.core.display.HTML object>"
173
+ ]
174
+ },
175
+ "metadata": {},
176
+ "output_type": "display_data"
177
+ },
178
+ {
179
+ "data": {
180
+ "text/html": [],
181
+ "text/plain": [
182
+ "<IPython.core.display.HTML object>"
183
+ ]
184
+ },
185
+ "metadata": {},
186
+ "output_type": "display_data"
187
+ },
188
+ {
189
+ "data": {
190
+ "text/plain": [
191
+ "{'Arcus': 0.0003855041868519038,\n",
192
+ " 'Cataract': 0.0005875547067262232,\n",
193
+ " 'Conjuctivities': 0.9942066669464111,\n",
194
+ " 'Eye Melanoma(Eye Cancer)': 0.0022827794309705496,\n",
195
+ " 'Normal Eye': 0.0025374265387654305}"
196
+ ]
197
+ },
198
+ "execution_count": 8,
199
+ "metadata": {},
200
+ "output_type": "execute_result"
201
+ }
202
+ ],
203
+ "source": [
204
+ "classify_image(im)"
205
+ ]
206
+ },
207
+ {
208
+ "cell_type": "code",
209
+ "execution_count": 9,
210
+ "id": "fe51f37c",
211
+ "metadata": {},
212
+ "outputs": [
213
+ {
214
+ "name": "stderr",
215
+ "output_type": "stream",
216
+ "text": [
217
+ "/home/shivam/mambaforge/lib/python3.10/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",
218
+ " warnings.warn(\n",
219
+ "/home/shivam/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: `optional` parameter is deprecated, and it has no effect\n",
220
+ " warnings.warn(value)\n",
221
+ "/home/shivam/mambaforge/lib/python3.10/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",
222
+ " warnings.warn(\n",
223
+ "/home/shivam/mambaforge/lib/python3.10/site-packages/gradio/deprecation.py:40: UserWarning: The 'type' parameter has been deprecated. Use the Number component instead.\n",
224
+ " warnings.warn(value)\n"
225
+ ]
226
+ },
227
+ {
228
+ "name": "stdout",
229
+ "output_type": "stream",
230
+ "text": [
231
+ "Running on local URL: http://127.0.0.1:7866\n",
232
+ "\n",
233
+ "To create a public link, set `share=True` in `launch()`.\n"
234
+ ]
235
+ },
236
+ {
237
+ "data": {
238
+ "text/plain": []
239
+ },
240
+ "execution_count": 9,
241
+ "metadata": {},
242
+ "output_type": "execute_result"
243
+ }
244
+ ],
245
+ "source": [
246
+ "#|export\n",
247
+ "image = gr.inputs.Image(shape=(192,192))\n",
248
+ "label = gr.outputs.Label()\n",
249
+ "examples = ['arcus.jpg','c.jpg','nik.jpg','conjuc.jpg','eyec.jpeg']\n",
250
+ "\n",
251
+ "intf = gr.Interface(fn = classify_image,inputs = image,outputs = label,examples= examples)\n",
252
+ "intf.launch(inline=False)"
253
+ ]
254
+ },
255
+ {
256
+ "cell_type": "code",
257
+ "execution_count": 16,
258
+ "id": "84c6d1a3",
259
+ "metadata": {
260
+ "scrolled": true
261
+ },
262
+ "outputs": [
263
+ {
264
+ "name": "stdout",
265
+ "output_type": "stream",
266
+ "text": [
267
+ "Export successful\n"
268
+ ]
269
+ }
270
+ ],
271
+ "source": [
272
+ "import nbdev\n",
273
+ "nbdev.export.nb_export('app.ipynb', 'app2.py')\n",
274
+ "print('Export successful')"
275
+ ]
276
+ },
277
+ {
278
+ "cell_type": "code",
279
+ "execution_count": 13,
280
+ "id": "b5dbe441",
281
+ "metadata": {},
282
+ "outputs": [
283
+ {
284
+ "ename": "ImportError",
285
+ "evalue": "cannot import name 'notebook2script' from 'nbdev.export' (/home/shivam/mambaforge/lib/python3.10/site-packages/nbdev/export.py)",
286
+ "output_type": "error",
287
+ "traceback": [
288
+ "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
289
+ "\u001b[0;31mImportError\u001b[0m Traceback (most recent call last)",
290
+ "Cell \u001b[0;32mIn[13], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mnbdev\u001b[39;00m\u001b[38;5;21;01m.\u001b[39;00m\u001b[38;5;21;01mexport\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m notebook2script\n\u001b[1;32m 2\u001b[0m notebook2script()\n",
291
+ "\u001b[0;31mImportError\u001b[0m: cannot import name 'notebook2script' from 'nbdev.export' (/home/shivam/mambaforge/lib/python3.10/site-packages/nbdev/export.py)"
292
+ ]
293
+ }
294
+ ],
295
+ "source": [
296
+ "from nbdev.export import notebook2script\n",
297
+ "notebook2script()"
298
+ ]
299
+ }
300
+ ],
301
+ "metadata": {
302
+ "kernelspec": {
303
+ "display_name": "Python 3 (ipykernel)",
304
+ "language": "python",
305
+ "name": "python3"
306
+ },
307
+ "language_info": {
308
+ "codemirror_mode": {
309
+ "name": "ipython",
310
+ "version": 3
311
+ },
312
+ "file_extension": ".py",
313
+ "mimetype": "text/x-python",
314
+ "name": "python",
315
+ "nbconvert_exporter": "python",
316
+ "pygments_lexer": "ipython3",
317
+ "version": "3.10.10"
318
+ }
319
+ },
320
+ "nbformat": 4,
321
+ "nbformat_minor": 5
322
+ }
app.py ADDED
@@ -0,0 +1,28 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
+ # %% ../app.ipynb 3
12
+ learn = load_learner('model.pkl')
13
+
14
+ # %% ../app.ipynb 6
15
+ categories = ('Arcus','Cataract','Conjuctivities','Eye Melanoma(Eye Cancer)','Normal Eye')
16
+
17
+ def classify_image(img):
18
+ pred,idx,probs = learn.predict(img)
19
+ return dict(zip(categories,map(float,probs)))
20
+
21
+
22
+ # %% ../app.ipynb 8
23
+ image = gr.inputs.Image(shape=(192,192))
24
+ label = gr.outputs.Label()
25
+ examples = ['arcus.jpg','c.jpg','nik.jpg','conjuc.jpg','eyec.jpeg']
26
+
27
+ intf = gr.Interface(fn = classify_image,inputs = image,outputs = label,examples= examples)
28
+ intf.launch(inline=False)
arcus.jpg ADDED
c.jpg ADDED
conjuc.jpg ADDED
eyec.jpeg ADDED
model.pkl ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ version https://git-lfs.github.com/spec/v1
2
+ oid sha256:ea8becf1fa870a0bf14144f01c81d09616bdf7461d714e57855629dbda3fbe01
3
+ size 46965181
model.pkl:Zone.Identifier ADDED
@@ -0,0 +1,3 @@
 
 
 
 
1
+ [ZoneTransfer]
2
+ ZoneId=3
3
+ HostUrl=https://www.kaggle.com/
nik.jpg ADDED