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Methane_Classifier
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  1. .ipynb_checkpoints/methane-plume-classification-yes-or-no-checkpoint.ipynb +312 -0
  2. methane-plume-classification-yes-or-no.ipynb +312 -0
  3. 01b85fbbaa5d9f3a0d8f.png → noplume1.png +0 -0
  4. 0021b95ff4079cc9b1b7.png → noplume2.png +0 -0
  5. GAO20200713t154610p0000-A_r3181_c599-plume.png → plume1.png +0 -0
  6. GAO20200714t150714p0000-A_r8908_c870-plume.png → plume2.png +0 -0
.ipynb_checkpoints/methane-plume-classification-yes-or-no-checkpoint.ipynb ADDED
@@ -0,0 +1,312 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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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": null,
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+ "metadata": {
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+ "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
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+ "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:12:56.482001Z",
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+ "iopub.status.busy": "2023-06-06T16:12:56.481629Z",
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+ "shell.execute_reply.started": "2023-06-06T16:12:56.481922Z"
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+ },
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+ "scrolled": true
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+ },
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+ "outputs": [],
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+ "source": [
20
+ "# This Python 3 environment comes with many helpful analytics libraries installed\n",
21
+ "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
22
+ "# For example, here's several helpful packages to load\n",
23
+ "\n",
24
+ "#import numpy as np # linear algebra\n",
25
+ "#import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
26
+ "\n",
27
+ "# Input data files are available in the read-only \"../input/\" directory\n",
28
+ "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
29
+ "\n",
30
+ "#import os\n",
31
+ "#for dirname, _, filenames in os.walk('/kaggle/input'):\n",
32
+ "# for filename in filenames:\n",
33
+ "# print(os.path.join(dirname, filename))\n",
34
+ "\n",
35
+ "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
36
+ "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
37
+ ]
38
+ },
39
+ {
40
+ "cell_type": "code",
41
+ "execution_count": null,
42
+ "metadata": {
43
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:12:56.515330Z",
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+ "iopub.status.busy": "2023-06-06T16:12:56.514653Z",
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+ "shell.execute_reply.started": "2023-06-06T16:12:56.515291Z"
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+ },
50
+ "scrolled": true
51
+ },
52
+ "outputs": [],
53
+ "source": [
54
+ "!pip install fastbook\n",
55
+ "import fastbook\n",
56
+ "import pandas as pd\n",
57
+ "import numpy as np\n",
58
+ "import os \n",
59
+ "\n",
60
+ "from fastbook import *\n",
61
+ "from fastai.vision.widgets import *\n",
62
+ "import gradio as gr"
63
+ ]
64
+ },
65
+ {
66
+ "cell_type": "code",
67
+ "execution_count": null,
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+ "metadata": {
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:17.047225Z",
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+ "iopub.status.busy": "2023-06-06T16:13:17.046261Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:17.047171Z"
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+ }
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+ },
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+ "outputs": [],
78
+ "source": [
79
+ "path = Path('/kaggle/input/speuntapped/train')"
80
+ ]
81
+ },
82
+ {
83
+ "cell_type": "code",
84
+ "execution_count": null,
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+ "metadata": {
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:17.058708Z",
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+ "iopub.status.busy": "2023-06-06T16:13:17.057847Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:17.058670Z"
92
+ }
93
+ },
94
+ "outputs": [],
95
+ "source": [
96
+ "fns = get_image_files(path)\n",
97
+ "fns"
98
+ ]
99
+ },
100
+ {
101
+ "cell_type": "code",
102
+ "execution_count": null,
103
+ "metadata": {
104
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:20.269200Z",
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+ "iopub.status.busy": "2023-06-06T16:13:20.267211Z",
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+ "shell.execute_reply": "2023-06-06T16:13:20.275708Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:20.269168Z"
110
+ }
111
+ },
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+ "outputs": [],
113
+ "source": [
114
+ "plume = DataBlock(\n",
115
+ " blocks=(ImageBlock, CategoryBlock),\n",
116
+ " get_items=get_image_files,\n",
117
+ " splitter=RandomSplitter(valid_pct=0.2,seed=42),\n",
118
+ " get_y=parent_label\n",
119
+ ")"
120
+ ]
121
+ },
122
+ {
123
+ "cell_type": "code",
124
+ "execution_count": null,
125
+ "metadata": {
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:20.279400Z",
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+ "iopub.status.busy": "2023-06-06T16:13:20.279013Z",
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+ "iopub.status.idle": "2023-06-06T16:13:20.294720Z",
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+ "shell.execute_reply": "2023-06-06T16:13:20.293498Z",
131
+ "shell.execute_reply.started": "2023-06-06T16:13:20.279361Z"
132
+ }
133
+ },
134
+ "outputs": [],
135
+ "source": [
136
+ "plume = plume.new(\n",
137
+ " item_tfms=RandomResizedCrop(152, min_scale=0.5),\n",
138
+ " batch_tfms=aug_transforms()\n",
139
+ ")"
140
+ ]
141
+ },
142
+ {
143
+ "cell_type": "code",
144
+ "execution_count": null,
145
+ "metadata": {
146
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:20.296793Z",
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+ "iopub.status.busy": "2023-06-06T16:13:20.296142Z",
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+ "iopub.status.idle": "2023-06-06T16:13:29.647446Z",
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+ "shell.execute_reply": "2023-06-06T16:13:29.646201Z",
151
+ "shell.execute_reply.started": "2023-06-06T16:13:20.296747Z"
152
+ }
153
+ },
154
+ "outputs": [],
155
+ "source": [
156
+ "dls = plume.dataloaders(path)"
157
+ ]
158
+ },
159
+ {
160
+ "cell_type": "code",
161
+ "execution_count": null,
162
+ "metadata": {
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:29.649289Z",
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+ "iopub.status.busy": "2023-06-06T16:13:29.648894Z",
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+ "iopub.status.idle": "2023-06-06T16:13:30.941482Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:29.649249Z"
169
+ }
170
+ },
171
+ "outputs": [],
172
+ "source": [
173
+ "dls.valid.show_batch(max_n=12, nrows=4) "
174
+ ]
175
+ },
176
+ {
177
+ "cell_type": "code",
178
+ "execution_count": null,
179
+ "metadata": {
180
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:30.942995Z",
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+ "iopub.status.busy": "2023-06-06T16:13:30.942633Z",
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+ "iopub.status.idle": "2023-06-06T16:16:55.896473Z",
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+ "shell.execute_reply": "2023-06-06T16:16:55.895239Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:30.942955Z"
186
+ }
187
+ },
188
+ "outputs": [],
189
+ "source": [
190
+ "learn = vision_learner(dls, resnet50, metrics=error_rate)\n",
191
+ "learn.fine_tune(epochs=3)"
192
+ ]
193
+ },
194
+ {
195
+ "cell_type": "code",
196
+ "execution_count": null,
197
+ "metadata": {
198
+ "execution": {
199
+ "iopub.execute_input": "2023-06-06T16:16:55.899023Z",
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+ "iopub.status.busy": "2023-06-06T16:16:55.898611Z",
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+ "iopub.status.idle": "2023-06-06T16:17:12.173908Z",
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+ "shell.execute_reply": "2023-06-06T16:17:12.172400Z",
203
+ "shell.execute_reply.started": "2023-06-06T16:16:55.898975Z"
204
+ }
205
+ },
206
+ "outputs": [],
207
+ "source": [
208
+ "from IPython.core.pylabtools import figsize \n",
209
+ "interp = ClassificationInterpretation.from_learner(learn)\n",
210
+ "interp.plot_confusion_matrix(figsize=(10,10))"
211
+ ]
212
+ },
213
+ {
214
+ "cell_type": "code",
215
+ "execution_count": null,
216
+ "metadata": {
217
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:17:12.177922Z",
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+ "iopub.status.busy": "2023-06-06T16:17:12.177508Z",
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+ "iopub.status.idle": "2023-06-06T16:17:13.734058Z",
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+ "shell.execute_reply": "2023-06-06T16:17:13.732857Z",
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+ "shell.execute_reply.started": "2023-06-06T16:17:12.177864Z"
223
+ }
224
+ },
225
+ "outputs": [],
226
+ "source": [
227
+ "interp.plot_top_losses(20, nrows=10, figsize=(20,20))"
228
+ ]
229
+ },
230
+ {
231
+ "cell_type": "code",
232
+ "execution_count": null,
233
+ "metadata": {
234
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:17:13.739200Z",
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+ "iopub.status.busy": "2023-06-06T16:17:13.735848Z",
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+ "iopub.status.idle": "2023-06-06T16:17:13.744700Z",
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+ "shell.execute_reply": "2023-06-06T16:17:13.743507Z",
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+ "shell.execute_reply.started": "2023-06-06T16:17:13.739151Z"
240
+ }
241
+ },
242
+ "outputs": [],
243
+ "source": [
244
+ "test_image = '/kaggle/input/speuntapped/test/test/ang20190922t192642-4_r4928_c373-plume.png'"
245
+ ]
246
+ },
247
+ {
248
+ "cell_type": "code",
249
+ "execution_count": null,
250
+ "metadata": {
251
+ "execution": {
252
+ "iopub.execute_input": "2023-06-06T16:17:13.750250Z",
253
+ "iopub.status.busy": "2023-06-06T16:17:13.749605Z",
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+ "iopub.status.idle": "2023-06-06T16:17:13.883090Z",
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+ "shell.execute_reply": "2023-06-06T16:17:13.881894Z",
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+ "shell.execute_reply.started": "2023-06-06T16:17:13.750206Z"
257
+ }
258
+ },
259
+ "outputs": [],
260
+ "source": [
261
+ "is_plume,_,probs = learn.predict(PILImage.create(test_image))\n",
262
+ "print(f\"This is a: {is_plume}.\")\n",
263
+ "print(f\"Probability it's a plume: {probs[1]:.4f}\")"
264
+ ]
265
+ },
266
+ {
267
+ "cell_type": "code",
268
+ "execution_count": null,
269
+ "metadata": {
270
+ "execution": {
271
+ "iopub.execute_input": "2023-06-06T16:22:39.764768Z",
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+ "iopub.status.busy": "2023-06-06T16:22:39.764285Z",
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+ "iopub.status.idle": "2023-06-06T16:22:40.137875Z",
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+ "shell.execute_reply": "2023-06-06T16:22:40.136697Z",
275
+ "shell.execute_reply.started": "2023-06-06T16:22:39.764726Z"
276
+ }
277
+ },
278
+ "outputs": [],
279
+ "source": [
280
+ "learn.export('methane plume detect.pkl')"
281
+ ]
282
+ },
283
+ {
284
+ "cell_type": "code",
285
+ "execution_count": null,
286
+ "metadata": {},
287
+ "outputs": [],
288
+ "source": []
289
+ }
290
+ ],
291
+ "metadata": {
292
+ "kernelspec": {
293
+ "display_name": "Python 3 (ipykernel)",
294
+ "language": "python",
295
+ "name": "python3"
296
+ },
297
+ "language_info": {
298
+ "codemirror_mode": {
299
+ "name": "ipython",
300
+ "version": 3
301
+ },
302
+ "file_extension": ".py",
303
+ "mimetype": "text/x-python",
304
+ "name": "python",
305
+ "nbconvert_exporter": "python",
306
+ "pygments_lexer": "ipython3",
307
+ "version": "3.10.9"
308
+ }
309
+ },
310
+ "nbformat": 4,
311
+ "nbformat_minor": 4
312
+ }
methane-plume-classification-yes-or-no.ipynb ADDED
@@ -0,0 +1,312 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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+ {
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+ {
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+ "cell_type": "code",
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+ "execution_count": null,
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+ "metadata": {
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+ "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
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+ "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:12:56.482001Z",
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+ "shell.execute_reply.started": "2023-06-06T16:12:56.481922Z"
15
+ },
16
+ "scrolled": true
17
+ },
18
+ "outputs": [],
19
+ "source": [
20
+ "# This Python 3 environment comes with many helpful analytics libraries installed\n",
21
+ "# It is defined by the kaggle/python Docker image: https://github.com/kaggle/docker-python\n",
22
+ "# For example, here's several helpful packages to load\n",
23
+ "\n",
24
+ "#import numpy as np # linear algebra\n",
25
+ "#import pandas as pd # data processing, CSV file I/O (e.g. pd.read_csv)\n",
26
+ "\n",
27
+ "# Input data files are available in the read-only \"../input/\" directory\n",
28
+ "# For example, running this (by clicking run or pressing Shift+Enter) will list all files under the input directory\n",
29
+ "\n",
30
+ "#import os\n",
31
+ "#for dirname, _, filenames in os.walk('/kaggle/input'):\n",
32
+ "# for filename in filenames:\n",
33
+ "# print(os.path.join(dirname, filename))\n",
34
+ "\n",
35
+ "# You can write up to 20GB to the current directory (/kaggle/working/) that gets preserved as output when you create a version using \"Save & Run All\" \n",
36
+ "# You can also write temporary files to /kaggle/temp/, but they won't be saved outside of the current session"
37
+ ]
38
+ },
39
+ {
40
+ "cell_type": "code",
41
+ "execution_count": null,
42
+ "metadata": {
43
+ "execution": {
44
+ "iopub.execute_input": "2023-06-06T16:12:56.515330Z",
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+ "iopub.status.busy": "2023-06-06T16:12:56.514653Z",
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+ "iopub.status.idle": "2023-06-06T16:13:17.032978Z",
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+ "shell.execute_reply": "2023-06-06T16:13:17.031623Z",
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+ "shell.execute_reply.started": "2023-06-06T16:12:56.515291Z"
49
+ },
50
+ "scrolled": true
51
+ },
52
+ "outputs": [],
53
+ "source": [
54
+ "!pip install fastbook\n",
55
+ "import fastbook\n",
56
+ "import pandas as pd\n",
57
+ "import numpy as np\n",
58
+ "import os \n",
59
+ "\n",
60
+ "from fastbook import *\n",
61
+ "from fastai.vision.widgets import *\n",
62
+ "import gradio as gr"
63
+ ]
64
+ },
65
+ {
66
+ "cell_type": "code",
67
+ "execution_count": null,
68
+ "metadata": {
69
+ "execution": {
70
+ "iopub.execute_input": "2023-06-06T16:13:17.047225Z",
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+ "iopub.status.busy": "2023-06-06T16:13:17.046261Z",
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+ "iopub.status.idle": "2023-06-06T16:13:17.053274Z",
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+ "shell.execute_reply": "2023-06-06T16:13:17.052116Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:17.047171Z"
75
+ }
76
+ },
77
+ "outputs": [],
78
+ "source": [
79
+ "path = Path('/kaggle/input/speuntapped/train')"
80
+ ]
81
+ },
82
+ {
83
+ "cell_type": "code",
84
+ "execution_count": null,
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+ "metadata": {
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+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:17.058708Z",
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+ "shell.execute_reply.started": "2023-06-06T16:13:17.058670Z"
92
+ }
93
+ },
94
+ "outputs": [],
95
+ "source": [
96
+ "fns = get_image_files(path)\n",
97
+ "fns"
98
+ ]
99
+ },
100
+ {
101
+ "cell_type": "code",
102
+ "execution_count": null,
103
+ "metadata": {
104
+ "execution": {
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+ "iopub.execute_input": "2023-06-06T16:13:20.269200Z",
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+ "iopub.status.busy": "2023-06-06T16:13:20.267211Z",
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+ "iopub.status.idle": "2023-06-06T16:13:20.276861Z",
108
+ "shell.execute_reply": "2023-06-06T16:13:20.275708Z",
109
+ "shell.execute_reply.started": "2023-06-06T16:13:20.269168Z"
110
+ }
111
+ },
112
+ "outputs": [],
113
+ "source": [
114
+ "plume = DataBlock(\n",
115
+ " blocks=(ImageBlock, CategoryBlock),\n",
116
+ " get_items=get_image_files,\n",
117
+ " splitter=RandomSplitter(valid_pct=0.2,seed=42),\n",
118
+ " get_y=parent_label\n",
119
+ ")"
120
+ ]
121
+ },
122
+ {
123
+ "cell_type": "code",
124
+ "execution_count": null,
125
+ "metadata": {
126
+ "execution": {
127
+ "iopub.execute_input": "2023-06-06T16:13:20.279400Z",
128
+ "iopub.status.busy": "2023-06-06T16:13:20.279013Z",
129
+ "iopub.status.idle": "2023-06-06T16:13:20.294720Z",
130
+ "shell.execute_reply": "2023-06-06T16:13:20.293498Z",
131
+ "shell.execute_reply.started": "2023-06-06T16:13:20.279361Z"
132
+ }
133
+ },
134
+ "outputs": [],
135
+ "source": [
136
+ "plume = plume.new(\n",
137
+ " item_tfms=RandomResizedCrop(152, min_scale=0.5),\n",
138
+ " batch_tfms=aug_transforms()\n",
139
+ ")"
140
+ ]
141
+ },
142
+ {
143
+ "cell_type": "code",
144
+ "execution_count": null,
145
+ "metadata": {
146
+ "execution": {
147
+ "iopub.execute_input": "2023-06-06T16:13:20.296793Z",
148
+ "iopub.status.busy": "2023-06-06T16:13:20.296142Z",
149
+ "iopub.status.idle": "2023-06-06T16:13:29.647446Z",
150
+ "shell.execute_reply": "2023-06-06T16:13:29.646201Z",
151
+ "shell.execute_reply.started": "2023-06-06T16:13:20.296747Z"
152
+ }
153
+ },
154
+ "outputs": [],
155
+ "source": [
156
+ "dls = plume.dataloaders(path)"
157
+ ]
158
+ },
159
+ {
160
+ "cell_type": "code",
161
+ "execution_count": null,
162
+ "metadata": {
163
+ "execution": {
164
+ "iopub.execute_input": "2023-06-06T16:13:29.649289Z",
165
+ "iopub.status.busy": "2023-06-06T16:13:29.648894Z",
166
+ "iopub.status.idle": "2023-06-06T16:13:30.941482Z",
167
+ "shell.execute_reply": "2023-06-06T16:13:30.940546Z",
168
+ "shell.execute_reply.started": "2023-06-06T16:13:29.649249Z"
169
+ }
170
+ },
171
+ "outputs": [],
172
+ "source": [
173
+ "dls.valid.show_batch(max_n=12, nrows=4) "
174
+ ]
175
+ },
176
+ {
177
+ "cell_type": "code",
178
+ "execution_count": null,
179
+ "metadata": {
180
+ "execution": {
181
+ "iopub.execute_input": "2023-06-06T16:13:30.942995Z",
182
+ "iopub.status.busy": "2023-06-06T16:13:30.942633Z",
183
+ "iopub.status.idle": "2023-06-06T16:16:55.896473Z",
184
+ "shell.execute_reply": "2023-06-06T16:16:55.895239Z",
185
+ "shell.execute_reply.started": "2023-06-06T16:13:30.942955Z"
186
+ }
187
+ },
188
+ "outputs": [],
189
+ "source": [
190
+ "learn = vision_learner(dls, resnet50, metrics=error_rate)\n",
191
+ "learn.fine_tune(epochs=3)"
192
+ ]
193
+ },
194
+ {
195
+ "cell_type": "code",
196
+ "execution_count": null,
197
+ "metadata": {
198
+ "execution": {
199
+ "iopub.execute_input": "2023-06-06T16:16:55.899023Z",
200
+ "iopub.status.busy": "2023-06-06T16:16:55.898611Z",
201
+ "iopub.status.idle": "2023-06-06T16:17:12.173908Z",
202
+ "shell.execute_reply": "2023-06-06T16:17:12.172400Z",
203
+ "shell.execute_reply.started": "2023-06-06T16:16:55.898975Z"
204
+ }
205
+ },
206
+ "outputs": [],
207
+ "source": [
208
+ "from IPython.core.pylabtools import figsize \n",
209
+ "interp = ClassificationInterpretation.from_learner(learn)\n",
210
+ "interp.plot_confusion_matrix(figsize=(10,10))"
211
+ ]
212
+ },
213
+ {
214
+ "cell_type": "code",
215
+ "execution_count": null,
216
+ "metadata": {
217
+ "execution": {
218
+ "iopub.execute_input": "2023-06-06T16:17:12.177922Z",
219
+ "iopub.status.busy": "2023-06-06T16:17:12.177508Z",
220
+ "iopub.status.idle": "2023-06-06T16:17:13.734058Z",
221
+ "shell.execute_reply": "2023-06-06T16:17:13.732857Z",
222
+ "shell.execute_reply.started": "2023-06-06T16:17:12.177864Z"
223
+ }
224
+ },
225
+ "outputs": [],
226
+ "source": [
227
+ "interp.plot_top_losses(20, nrows=10, figsize=(20,20))"
228
+ ]
229
+ },
230
+ {
231
+ "cell_type": "code",
232
+ "execution_count": null,
233
+ "metadata": {
234
+ "execution": {
235
+ "iopub.execute_input": "2023-06-06T16:17:13.739200Z",
236
+ "iopub.status.busy": "2023-06-06T16:17:13.735848Z",
237
+ "iopub.status.idle": "2023-06-06T16:17:13.744700Z",
238
+ "shell.execute_reply": "2023-06-06T16:17:13.743507Z",
239
+ "shell.execute_reply.started": "2023-06-06T16:17:13.739151Z"
240
+ }
241
+ },
242
+ "outputs": [],
243
+ "source": [
244
+ "test_image = '/kaggle/input/speuntapped/test/test/ang20190922t192642-4_r4928_c373-plume.png'"
245
+ ]
246
+ },
247
+ {
248
+ "cell_type": "code",
249
+ "execution_count": null,
250
+ "metadata": {
251
+ "execution": {
252
+ "iopub.execute_input": "2023-06-06T16:17:13.750250Z",
253
+ "iopub.status.busy": "2023-06-06T16:17:13.749605Z",
254
+ "iopub.status.idle": "2023-06-06T16:17:13.883090Z",
255
+ "shell.execute_reply": "2023-06-06T16:17:13.881894Z",
256
+ "shell.execute_reply.started": "2023-06-06T16:17:13.750206Z"
257
+ }
258
+ },
259
+ "outputs": [],
260
+ "source": [
261
+ "is_plume,_,probs = learn.predict(PILImage.create(test_image))\n",
262
+ "print(f\"This is a: {is_plume}.\")\n",
263
+ "print(f\"Probability it's a plume: {probs[1]:.4f}\")"
264
+ ]
265
+ },
266
+ {
267
+ "cell_type": "code",
268
+ "execution_count": null,
269
+ "metadata": {
270
+ "execution": {
271
+ "iopub.execute_input": "2023-06-06T16:22:39.764768Z",
272
+ "iopub.status.busy": "2023-06-06T16:22:39.764285Z",
273
+ "iopub.status.idle": "2023-06-06T16:22:40.137875Z",
274
+ "shell.execute_reply": "2023-06-06T16:22:40.136697Z",
275
+ "shell.execute_reply.started": "2023-06-06T16:22:39.764726Z"
276
+ }
277
+ },
278
+ "outputs": [],
279
+ "source": [
280
+ "learn.export('methane plume detect.pkl')"
281
+ ]
282
+ },
283
+ {
284
+ "cell_type": "code",
285
+ "execution_count": null,
286
+ "metadata": {},
287
+ "outputs": [],
288
+ "source": []
289
+ }
290
+ ],
291
+ "metadata": {
292
+ "kernelspec": {
293
+ "display_name": "Python 3 (ipykernel)",
294
+ "language": "python",
295
+ "name": "python3"
296
+ },
297
+ "language_info": {
298
+ "codemirror_mode": {
299
+ "name": "ipython",
300
+ "version": 3
301
+ },
302
+ "file_extension": ".py",
303
+ "mimetype": "text/x-python",
304
+ "name": "python",
305
+ "nbconvert_exporter": "python",
306
+ "pygments_lexer": "ipython3",
307
+ "version": "3.10.9"
308
+ }
309
+ },
310
+ "nbformat": 4,
311
+ "nbformat_minor": 4
312
+ }
01b85fbbaa5d9f3a0d8f.png → noplume1.png RENAMED
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0021b95ff4079cc9b1b7.png → noplume2.png RENAMED
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GAO20200713t154610p0000-A_r3181_c599-plume.png → plume1.png RENAMED
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GAO20200714t150714p0000-A_r8908_c870-plume.png → plume2.png RENAMED
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