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Browse files- __pycache__/solver.cpython-310.pyc +0 -0
- app.py +2 -2
- output/Tablero_solucion.png +0 -0
- solver.py +4 -10
- wordsPuzzle/ALDRIN.jpg +0 -0
- wordsPuzzle/BARNEY.jpg +0 -0
- wordsPuzzle/LAWYER.jpg +0 -0
- wordsPuzzle/LILY.jpg +0 -0
- wordsPuzzle/MANHATTAN.jpg +0 -0
- wordsPuzzle/MARSHALL.jpg +0 -0
- wordsPuzzle/MOSBY.jpg +0 -0
- wordsPuzzle/PRESENTER.jpg +0 -0
- wordsPuzzle/SCHERBATSKY.jpg +0 -0
- wordsPuzzle/TEACHER.jpg +0 -0
- wordsPuzzle/TED.jpg +0 -0
__pycache__/solver.cpython-310.pyc
ADDED
Binary file (6.01 kB). View file
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app.py
CHANGED
@@ -62,14 +62,14 @@ def main():
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input_board = gr.Image(label='Board',
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type='filepath',
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interactive=True,
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-
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with gr.Row():
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crop_board_button = gr.Button('Crop Board ✂️')
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with gr.Row():
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input_words = gr.Image(label='Words',
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type='filepath',
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interactive=True, height="300px", width="300px",
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-
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with gr.Row():
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crop_words_button = gr.Button('Crop Words ✂️')
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with gr.Row():
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input_board = gr.Image(label='Board',
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type='filepath',
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interactive=True,
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)
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with gr.Row():
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crop_board_button = gr.Button('Crop Board ✂️')
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with gr.Row():
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input_words = gr.Image(label='Words',
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type='filepath',
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interactive=True, height="300px", width="300px",
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)
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with gr.Row():
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crop_words_button = gr.Button('Crop Words ✂️')
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with gr.Row():
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output/Tablero_solucion.png
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solver.py
CHANGED
@@ -19,7 +19,7 @@ with open("class_names.txt", "r") as f: # reading them in from class_names.txt
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model1 = tf.keras.models.load_model('model/model30.h5')
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model2 = tf.keras.models.load_model('model/model15.h5')
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model3 = tf.keras.models.load_model('model/model2.h5')
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palabras_1 = []
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# Borrar el directorio de imagenes
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@@ -177,18 +177,12 @@ def solve_puzzle(img, words):
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img_array = img2.reshape(1, 28, 28, 1)
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prediction1 = np.argmax(model1.predict(img_array))
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prediction2 = np.argmax(model2.predict(img_array))
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prediction3 = np.argmax(model3.predict(img_array))
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pred = 0
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if prediction1 == prediction2
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pred = prediction1
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elif prediction1 == prediction2:
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pred = prediction1
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elif prediction2 == prediction3:
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pred = prediction2
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elif prediction1 == prediction3:
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pred = prediction3
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else:
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-
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#print(characters[pred])
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contCuadrados["anchura"] = x
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contCuadrados["altura"] = y
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model1 = tf.keras.models.load_model('model/model30.h5')
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model2 = tf.keras.models.load_model('model/model15.h5')
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#model3 = tf.keras.models.load_model('model/model2.h5')
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palabras_1 = []
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# Borrar el directorio de imagenes
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img_array = img2.reshape(1, 28, 28, 1)
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prediction1 = np.argmax(model1.predict(img_array))
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prediction2 = np.argmax(model2.predict(img_array))
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#prediction3 = np.argmax(model3.predict(img_array))
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pred = 0
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if prediction1 == prediction2:
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pred = prediction1
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else:
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pred = 32
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#print(characters[pred])
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contCuadrados["anchura"] = x
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contCuadrados["altura"] = y
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wordsPuzzle/ALDRIN.jpg
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wordsPuzzle/BARNEY.jpg
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wordsPuzzle/LAWYER.jpg
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wordsPuzzle/LILY.jpg
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wordsPuzzle/MANHATTAN.jpg
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wordsPuzzle/MARSHALL.jpg
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wordsPuzzle/MOSBY.jpg
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wordsPuzzle/PRESENTER.jpg
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wordsPuzzle/SCHERBATSKY.jpg
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wordsPuzzle/TEACHER.jpg
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wordsPuzzle/TED.jpg
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