from experiment2.model_em2 import FcCvModel
import numpy as np
import matplotlib.pyplot as plt


# 1024*33*10240
data = np.load("")
labels = np.load()

test_data = data[896:]
test_y = data[896:]

model = FcCvModel()
model.load_weights('weights_1000')
y_test_pred = model(test_data)

num = 0

x,y,r = y_test_pred[num][0],y_test_pred[num][1],y_test_pred[num][2]
vp = np.ones((1024,1024),dtype=np.float32)
for i in range(x-r,x+r):
    for j in range(y-r,y+r):
        if (i-x)**2+(j-y)**2<r**2:
            vp[i,j] = 1

plt.figure(figsize=(18,12))
plt.subplot(1, 2, 1)
plt.title('预测位置')
plt.ylabel("深度")
plt.xlabel("水平")
plt.imshow(vp)

x,y,r = test_y[num][0],test_y[num][1],test_y[num][2]
vp = np.ones((1024,1024),dtype=np.float32)
for i in range(x-r,x+r):
    for j in range(y-r,y+r):
        if (i-x)**2+(j-y)**2<r**2:
            vp[i,j] = 1

plt.subplot(1, 2, 2)
plt.title('实际位置')
plt.ylabel("深度")
plt.xlabel("水平")
plt.imshow(vp)
plt.show()


f6e31ccccebf2c539429d12c83be9e002667478b
<mask token>

<mask token>
model.load_weights('weights_1000')
<mask token>
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.figure(figsize=(18, 12))
plt.subplot(1, 2, 1)
plt.title('预测位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
<mask token>
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.subplot(1, 2, 2)
plt.title('实际位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
plt.show()

<mask token>
data = np.load('')
labels = np.load()
test_data = data[896:]
test_y = data[896:]
model = FcCvModel()
model.load_weights('weights_1000')
y_test_pred = model(test_data)
num = 0
x, y, r = y_test_pred[num][0], y_test_pred[num][1], y_test_pred[num][2]
vp = np.ones((1024, 1024), dtype=np.float32)
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.figure(figsize=(18, 12))
plt.subplot(1, 2, 1)
plt.title('预测位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
x, y, r = test_y[num][0], test_y[num][1], test_y[num][2]
vp = np.ones((1024, 1024), dtype=np.float32)
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.subplot(1, 2, 2)
plt.title('实际位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
plt.show()

from experiment2.model_em2 import FcCvModel
import numpy as np
import matplotlib.pyplot as plt
data = np.load('')
labels = np.load()
test_data = data[896:]
test_y = data[896:]
model = FcCvModel()
model.load_weights('weights_1000')
y_test_pred = model(test_data)
num = 0
x, y, r = y_test_pred[num][0], y_test_pred[num][1], y_test_pred[num][2]
vp = np.ones((1024, 1024), dtype=np.float32)
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.figure(figsize=(18, 12))
plt.subplot(1, 2, 1)
plt.title('预测位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
x, y, r = test_y[num][0], test_y[num][1], test_y[num][2]
vp = np.ones((1024, 1024), dtype=np.float32)
for i in range(x - r, x + r):
    for j in range(y - r, y + r):
        if (i - x) ** 2 + (j - y) ** 2 < r ** 2:
            vp[i, j] = 1
plt.subplot(1, 2, 2)
plt.title('实际位置')
plt.ylabel('深度')
plt.xlabel('水平')
plt.imshow(vp)
plt.show()

from experiment2.model_em2 import FcCvModel
import numpy as np
import matplotlib.pyplot as plt


# 1024*33*10240
data = np.load("")
labels = np.load()

test_data = data[896:]
test_y = data[896:]

model = FcCvModel()
model.load_weights('weights_1000')
y_test_pred = model(test_data)

num = 0

x,y,r = y_test_pred[num][0],y_test_pred[num][1],y_test_pred[num][2]
vp = np.ones((1024,1024),dtype=np.float32)
for i in range(x-r,x+r):
    for j in range(y-r,y+r):
        if (i-x)**2+(j-y)**2<r**2:
            vp[i,j] = 1

plt.figure(figsize=(18,12))
plt.subplot(1, 2, 1)
plt.title('预测位置')
plt.ylabel("深度")
plt.xlabel("水平")
plt.imshow(vp)

x,y,r = test_y[num][0],test_y[num][1],test_y[num][2]
vp = np.ones((1024,1024),dtype=np.float32)
for i in range(x-r,x+r):
    for j in range(y-r,y+r):
        if (i-x)**2+(j-y)**2<r**2:
            vp[i,j] = 1

plt.subplot(1, 2, 2)
plt.title('实际位置')
plt.ylabel("深度")
plt.xlabel("水平")
plt.imshow(vp)
plt.show()

