fix bug
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6e7357b250
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7919878582
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@ -13,7 +13,7 @@ dataset_path = sys.argv[1]
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print(dataset_path)
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timestamps = np.loadtxt(dataset_path + '/mav0/cam0/data.csv', usecols=[0], delimiter=',', dtype=np.int64)
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exposures = np.loadtxt(dataset_path + '/mav0/cam0/exposure.csv', usecols=[1], delimiter=',', dtype=np.int64).astype(np.float64) * 1e-9
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exposures = np.loadtxt(dataset_path + '/mav0/cam0/exposure.csv', usecols=[1], delimiter=',', dtype=np.int64).astype(np.float64) * 1e-6
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pixel_avgs = list()
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if timestamps.shape[0] != exposures.shape[0]: print("timestamps and exposures do not match")
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@ -34,21 +34,23 @@ print(imgs.dtype)
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inv_resp = np.arange(256, dtype=np.float64)
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inv_resp[250:] = -1.0 # Use negative numbers to detect oversaturation
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irradiance = imgs[0] / exposures[0]
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def opt_irradiance():
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corrected_imgs = inv_resp[imgs] * exposures[:, np.newaxis, np.newaxis]
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times = np.ones_like(corrected_imgs) * (exposures**2)[:, np.newaxis, np.newaxis]
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times[corrected_imgs < 0] == 0
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corrected_imgs[corrected_imgs < 0] == 0
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irr = np.sum(corrected_imgs, axis=0) / np.sum(times, axis=0)
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times[corrected_imgs < 0] = 0
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corrected_imgs[corrected_imgs < 0] = 0
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denom = np.sum(times, axis=0)
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irr = np.sum(corrected_imgs, axis=0) / denom
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irr[denom == 0] = -1.0
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return irr
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def opt_inv_resp():
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generated_imgs = irradiance[np.newaxis, :, :] * exposures[:, np.newaxis, np.newaxis]
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num_pixels_by_intensity = np.bincount(imgs.flat)
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num_pixels_by_intensity = np.bincount(imgs.flat, generated_imgs.flat >= 0)
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sum_by_intensity = np.bincount(imgs.flat, generated_imgs.flat)
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new_inv_resp = inv_resp
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@ -64,7 +66,6 @@ def print_error():
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generated_imgs[imgs == 255] = 0
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print(np.sum(generated_imgs**2))
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print_error()
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for iter in range(3):
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irradiance = opt_irradiance()
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print_error()
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@ -72,6 +73,7 @@ for iter in range(3):
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print_error()
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plt.figure()
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plt.plot(inv_resp)
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plt.ylabel('Img Mean')
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