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759fb41
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1 Parent(s): 47efdff

Update app.py

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  1. app.py +42 -181
app.py CHANGED
@@ -4,11 +4,11 @@ from keras.models import load_model
4
  import numpy as np
5
 
6
  # Load the pre-trained model from the local path
7
- model_path = 'Mango.h5'
8
  model = load_model(model_path) # Load the model here
9
 
10
  def predict_disease(image_file, model, all_labels):
11
-
12
  try:
13
  # Load and preprocess the image
14
  img = load_img(image_file, target_size=(224, 224)) # Use load_img from tensorflow.keras.utils
@@ -24,53 +24,11 @@ def predict_disease(image_file, model, all_labels):
24
  predicted_label = all_labels[predicted_class]
25
 
26
  # Print the predicted label to the console
27
-
28
- if predicted_label=='Mango Anthracrose':
29
- predicted_label = """<style>
30
- li{
31
- font-size: 15px;
32
- margin-left: 90px;
33
- margin-top: 15px;
34
- margin-bottom: 15px;
35
- }
36
- h4{
37
- font-size: 17px;
38
- margin-top: 15px;
39
- }
40
- h4:hover{
41
- cursor: pointer;
42
- }
43
-
44
- h3:hover{
45
- cursor: pointer;
46
- color: blue;
47
- transform: scale(1.3);
48
- }
49
- .note{
50
- text-align: center;
51
- font-size: 16px;
52
- }
53
- p{
54
- font-size: 13px;
55
- text-align: center;
56
- }
57
-
58
- </style>
59
- <h3><center><b>Mango Anthracrose</b></center></h3>
60
- <h4>PESTICIDES TO BE USED:</h4>
61
- <ul>
62
- <li>1. Mancozeb</li>
63
- <li>2. Azoxystrobin</li>
64
- <li>3. carbendazim</li>
65
- <li>4. Propiconazole</li>
66
- <li>5. Thiophanate-methyl</li>
67
- <li>6. Copper Sulfate</li>
68
- </ul><br>
69
- <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
70
- <p>Be sure to follow local regulations and guidelines for application</p>
71
 
72
- """
73
- elif predicted_label=='Mango Bacterial Canker':
 
 
74
  predicted_label = """
75
  <style>
76
  li{
@@ -102,70 +60,23 @@ def predict_disease(image_file, model, all_labels):
102
  }
103
 
104
  </style>
105
- <h3><center><b>Mango Bacterial Canker</b></center></h3>
106
  <h4>PESTICIDES TO BE USED:</h4>
107
  <ul>
108
- <li>1. Copper Hydroxide</li>
109
- <li>2. Copper Oxychloride</li>
110
- <li>3. Streptomycin</li>
111
- <li>4. oxytetracycline</li>
112
- <li>5. Neem oil</li>
113
- <li>6. Garlic oil</li>
114
- </ul>
115
- <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
116
- <p>Be sure to follow local regulations and guidelines for application</p>
117
-
118
-
119
- """
120
- elif predicted_label=='Mango Cutting Weevil':
121
- predicted_label = """
122
- <style>
123
- li{
124
- font-size: 15px;
125
- margin-left: 90px;
126
- margin-top: 15px;
127
- margin-bottom: 15px;
128
- }
129
- h4{
130
- font-size: 17px;
131
- margin-top: 15px;
132
- }
133
- h4:hover{
134
- cursor: pointer;
135
- }
136
 
137
- h3:hover{
138
- cursor: pointer;
139
- color: blue;
140
- transform: scale(1.3);
141
- }
142
- .note{
143
- text-align: center;
144
- font-size: 16px;
145
- }
146
- p{
147
- font-size: 13px;
148
- text-align: center;
149
- }
150
 
151
- </style>
152
- <h3><center><b>Mango Cutting Weevil</b></center></h3>
153
- <h4>PESTICIDES TO BE USED:</h4>
154
- <ul>
155
- <li>1. Imidacloprid</li>
156
- <li>2. Thiamethoxam</li>
157
- <li>3. Chlorpyrifos</li>
158
- <li>4. Lambda-cyhalothrin</li>
159
- <li>5. Fipronil</li>
160
- <li>6. Neem oil</li>
161
  </ul>
162
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
163
  <p>Be sure to follow local regulations and guidelines for application</p>
164
 
165
 
166
  """
167
-
168
- elif predicted_label=='Mango Die Back':
169
  predicted_label = """
170
  <style>
171
  li{
@@ -197,22 +108,22 @@ def predict_disease(image_file, model, all_labels):
197
  }
198
 
199
  </style>
200
- <h3><center><b>Mango Die Back</b></center></h3>
201
  <h4>PESTICIDES TO BE USED:</h4>
202
  <ul>
203
- <li>1. Carbendazim</li>
204
- <li>2. Mancozeb</li>
205
  <li>3. Azoxystrobin</li>
206
- <li>4. Triazole</li>
207
- <li>5. Potassium bicarbonate</li>
208
- <li>6. Sodium bicarbonate</li>
209
  </ul>
210
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
211
  <p>Be sure to follow local regulations and guidelines for application</p>
212
 
213
 
214
  """
215
- elif predicted_label=='Mango Gall Midge':
216
  predicted_label = """
217
  <style>
218
  li{
@@ -244,22 +155,22 @@ def predict_disease(image_file, model, all_labels):
244
  }
245
 
246
  </style>
247
- <h3><center><b>Mango Gall Midge</b></center></h3>
248
  <h4>PESTICIDES TO BE USED:</h4>
249
  <ul>
250
- <li>1. Imidacloprid</li>
251
- <li>2. Thiamethoxam</li>
252
- <li>3. Chlorpyrifos</li>
253
- <li>4. Lambda-cyhalothrin</li>
254
- <li>5. Spinosad</li>
255
- <li>6. Pyrethrin</li>
256
  </ul>
257
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
258
  <p>Be sure to follow local regulations and guidelines for application</p>
259
 
260
 
261
  """
262
- elif predicted_label=='Mango Powdery Mildew':
263
  predicted_label = """
264
  <style>
265
  li{
@@ -291,72 +202,26 @@ def predict_disease(image_file, model, all_labels):
291
  }
292
 
293
  </style>
294
- <h3><center><b>Mango Powdery Mildew</b></center></h3>
295
  <h4>PESTICIDES TO BE USED:</h4>
296
  <ul>
297
- <li>1. Sulfur</li>
298
- <li>2. Bicarbonates</li>
299
- <li>3. Myclobutanil</li>
300
- <li>4. Triadimefon</li>
301
- <li>5. Propiconazole</li>
302
- <li>6. Azoxystrobin</li>
303
- </ul>
304
- <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
305
- <p>Be sure to follow local regulations and guidelines for application</p>
306
-
307
-
308
- """
309
-
310
- elif predicted_label=='Mango Sooty Mould':
311
- predicted_label = """
312
- <style>
313
- li{
314
- font-size: 15px;
315
- margin-left: 90px;
316
- margin-top: 15px;
317
- margin-bottom: 15px;
318
- }
319
- h4{
320
- font-size: 17px;
321
- margin-top: 15px;
322
- }
323
- h4:hover{
324
- cursor: pointer;
325
- }
326
 
327
- h3:hover{
328
- cursor: pointer;
329
- color: blue;
330
- transform: scale(1.3);
331
- }
332
- .note{
333
- text-align: center;
334
- font-size: 16px;
335
- }
336
- p{
337
- font-size: 13px;
338
- text-align: center;
339
- }
340
 
341
- </style>
342
- <h3><center><b>Mango Sooty Mould</b></center></h3>
343
- <h4>PESTICIDES TO BE USED:</h4>
344
- <ul>
345
- <li>1. Imidacloprid (Neonicotinoid)</li>
346
- <li>2. Thiamethoxam (Neonicotinoid)</li>
347
- <li>3. Bifenthrin (Pyrethroid)</li>
348
- <li>4. Lambda-cyhalothrin (Pyrethroid)</li>
349
- <li>5. Insecticidal soap</li>
350
- <li>6. Horticultural oil</li>
351
  </ul>
352
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
353
  <p>Be sure to follow local regulations and guidelines for application</p>
354
 
355
 
356
  """
 
 
357
  else:
358
- predicted_label = """<h3 align="center">Mango Healthy</h3><br><br>
359
- <center>No need use Pesticides</center>"""
360
 
361
  return predicted_label
362
 
@@ -367,14 +232,10 @@ def predict_disease(image_file, model, all_labels):
367
 
368
  # List of class labels
369
  all_labels = [
370
- 'Mango Anthracrose',
371
- 'Mango Bacterial Canker',
372
- 'Mango Cutting Weevil',
373
- 'Mango Die Back',
374
- 'Mango Gall Midge',
375
- 'Mango Healthy',
376
- 'Mango Powdery Mildew',
377
- 'Mango Sooty Mould'
378
  ]
379
 
380
  # Define the Gradio interface
@@ -386,7 +247,7 @@ gr_interface = gr.Interface(
386
  fn=gradio_predict, # Function to call for predictions
387
  inputs=gr.Image(type="filepath"), # Upload image as file path
388
  outputs="html", # Output will be the class label as text
389
- title="""<center>Mango Disease Predictor</center>""",
390
  description="Upload an image of a plant to predict the disease.",
391
  )
392
 
 
4
  import numpy as np
5
 
6
  # Load the pre-trained model from the local path
7
+ model_path = 'chilli.h5'
8
  model = load_model(model_path) # Load the model here
9
 
10
  def predict_disease(image_file, model, all_labels):
11
+
12
  try:
13
  # Load and preprocess the image
14
  img = load_img(image_file, target_size=(224, 224)) # Use load_img from tensorflow.keras.utils
 
24
  predicted_label = all_labels[predicted_class]
25
 
26
  # Print the predicted label to the console
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
27
 
28
+ if predicted_label=='Chilli Healthy':
29
+ predicted_label = predicted_label = """<h3 align="center">Chilli Healthy</h3><br><br>
30
+ <center>No need use Pesticides</center>"""
31
+ elif predicted_label=='Chilli Yellowish':
32
  predicted_label = """
33
  <style>
34
  li{
 
60
  }
61
 
62
  </style>
63
+ <h3><center><b>Chilli Yellowish</b></center></h3>
64
  <h4>PESTICIDES TO BE USED:</h4>
65
  <ul>
66
+ <li>1. Chlorothalonil (Daconil)</li>
67
+ <li>2. Mancozeb (Dithane)</li>
68
+ <li>3. Copper oxychloride (Kocide)</li>
69
+ <li>4. Azoxystrobin (Heritage)</li>
70
+ <li>5. Pyraclostrobin (Cabrio)</li>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
71
 
 
 
 
 
 
 
 
 
 
 
 
 
 
72
 
 
 
 
 
 
 
 
 
 
 
73
  </ul>
74
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
75
  <p>Be sure to follow local regulations and guidelines for application</p>
76
 
77
 
78
  """
79
+ elif predicted_label=='Chilli whitefly':
 
80
  predicted_label = """
81
  <style>
82
  li{
 
108
  }
109
 
110
  </style>
111
+ <h3><center><b>Chilli whitefly</b></center></h3>
112
  <h4>PESTICIDES TO BE USED:</h4>
113
  <ul>
114
+ <li>1. Copper oxychloride (Kocide)</li>
115
+ <li>2. Mancozeb(Dithane)</li>
116
  <li>3. Azoxystrobin</li>
117
+ <li>4. Chlorothalonil</li>
118
+
119
+
120
  </ul>
121
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
122
  <p>Be sure to follow local regulations and guidelines for application</p>
123
 
124
 
125
  """
126
+ elif predicted_label=='Chilli leaf Spot':
127
  predicted_label = """
128
  <style>
129
  li{
 
155
  }
156
 
157
  </style>
158
+ <h3><center><b>Chilli leaf Spot</b></center></h3>
159
  <h4>PESTICIDES TO BE USED:</h4>
160
  <ul>
161
+ <li>1. Copper oxychloride (Kocide)</li>
162
+ <li>2. Mancozeb(Dithane)</li>
163
+ <li>3. Azoxystrobin</li>
164
+ <li>4. Chlorothalonil</li>
165
+
166
+
167
  </ul>
168
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
169
  <p>Be sure to follow local regulations and guidelines for application</p>
170
 
171
 
172
  """
173
+ elif predicted_label=='Chilli Leaf Curl':
174
  predicted_label = """
175
  <style>
176
  li{
 
202
  }
203
 
204
  </style>
205
+ <h3><center><b>Chilli Leaf Curl</b></center></h3>
206
  <h4>PESTICIDES TO BE USED:</h4>
207
  <ul>
208
+ <li>1. Copper oxychloride (Kocide)</li>
209
+ <li>2. Mancozeb(Dithane)</li>
210
+ <li>3. Azoxystrobin</li>
211
+ <li>4. Chlorothalonil</li>
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
212
 
 
 
 
 
 
 
 
 
 
 
 
 
 
213
 
 
 
 
 
 
 
 
 
 
 
214
  </ul>
215
  <p class="note"><b>* * * IMPORTANT NOTE * * *</b></p>
216
  <p>Be sure to follow local regulations and guidelines for application</p>
217
 
218
 
219
  """
220
+
221
+
222
  else:
223
+ predicted_label = """<h3 align="center">Choose Correct image</h3><br><br>
224
+ """
225
 
226
  return predicted_label
227
 
 
232
 
233
  # List of class labels
234
  all_labels = [
235
+ 'Chilli Yellowish',
236
+ 'Chilli whitefly',
237
+ 'Chilli leaf Spot','Chilli Leaf Curl',
238
+ 'Chilli Healthy'
 
 
 
 
239
  ]
240
 
241
  # Define the Gradio interface
 
247
  fn=gradio_predict, # Function to call for predictions
248
  inputs=gr.Image(type="filepath"), # Upload image as file path
249
  outputs="html", # Output will be the class label as text
250
+ title="Chilli Disease Predictor",
251
  description="Upload an image of a plant to predict the disease.",
252
  )
253