diff --git a/code/event_videos.py b/code/event_videos.py
index d89815e..86885a6 100644
--- a/code/event_videos.py
+++ b/code/event_videos.py
@@ -1,6 +1,7 @@
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
+# from matplotlib.patches import patch
import os
import sys
import cv2
@@ -9,6 +10,8 @@ import argparse
from IPython import embed
from tqdm import tqdm
from thunderfish.powerspectrum import decibel
+import pathlib
+import pandas as pd
def main(folder, dt):
video_path = glob.glob(os.path.join(folder, '2022*.mp4'))[0]
@@ -16,136 +19,317 @@ def main(folder, dt):
if not os.path.exists(create_video_path):
os.mkdir(create_video_path)
- # embed()
- # quit()
+
video = cv2.VideoCapture(video_path) # was 'cap'
# fish_freqs = np.load(os.path.join(folder, 'analysis', 'fish_freq_interp.npy'))
fish_freqs = np.load(os.path.join(folder, 'analysis', 'fish_freq.npy'))
- rise_idx = np.load(os.path.join(folder, 'analysis', 'rise_idx.npy'))
+
+ # rise_idx = np.load(os.path.join(folder, 'analysis', 'rise_idx.npy'))
+ meta = pd.read_csv(pathlib.Path(folder).parent / 'meta.csv', sep=',', encoding='utf-7', index_col=0)
+ filename = pathlib.Path(folder).name
+ win_id = meta.loc[filename, 'Win_ID']
+ lose_id = meta.loc[filename, 'Lose_ID']
+ rise_bboxes = pd.read_csv(pathlib.Path(folder) / "risedetector_bboxes.csv", sep=',')
+ chirp_bboxes = pd.read_csv(pathlib.Path(folder) / "chirpdetector_bboxes.csv", sep=',')
+ rise_times = rise_bboxes['t0'][rise_bboxes['id'] == lose_id].to_numpy()
+ chirp_times = chirp_bboxes['chirp_times'][(chirp_bboxes['assigned_track'] == lose_id)].to_numpy()
+
+ # ToDo: rise and chipt times to times idxs!!!
+ # embed()
+ # quit()
+
frame_times = np.load(os.path.join(folder, 'analysis', 'frame_times.npy'))
- times = np.load(os.path.join(folder, 'times.npy'))
+ times = np.load(os.path.join(folder, 'times.npy'))
fill_freqs = np.load(os.path.join(folder, 'fill_freqs.npy'))
fill_times = np.load(os.path.join(folder, 'fill_times.npy'))
fill_spec_shape = np.load(os.path.join(folder, 'fill_spec_shape.npy'))
fill_spec = np.memmap(os.path.join(folder, 'fill_spec.npy'), dtype='float', mode='r',
shape=(fill_spec_shape[0], fill_spec_shape[1]), order='F')
- #######################################
- # embed()
- # quit()
- for fish_nr in np.arange(2)[::-1]:
-
- for idx_oi in tqdm(np.array(rise_idx[fish_nr][~np.isnan(rise_idx[fish_nr])], dtype=int)):
- time_oi = times[idx_oi]
-
- HH = int((time_oi / 3600) // 1)
- MM = int((time_oi - HH * 3600) // 60)
- SS = int(time_oi - HH * 3600 - MM * 60)
-
- frames_oi = np.arange(len(frame_times))[np.abs(frame_times - time_oi) <= dt]
- idxs_oi = np.arange(len(times))[np.abs(times - time_oi) <= dt*3]
-
- fig = plt.figure(figsize=(16*2/2.54, 9*2/2.54))
- gs = gridspec.GridSpec(6, 2, left=0.075, bottom=0.05, right=1, top=0.95, width_ratios=(1.5, 3), hspace=.3, wspace=0.05)
- ax = []
- ax.append(fig.add_subplot(gs[:, 1]))
- ax.append(fig.add_subplot(gs[1:3, 0]))
- ax.append(fig.add_subplot(gs[3:5, 0]))
-
-
- y00, y01 = np.nanmin(fish_freqs[0][idxs_oi]), np.nanmax(fish_freqs[0][idxs_oi])
- y10, y11 = np.nanmin(fish_freqs[1][idxs_oi]), np.nanmax(fish_freqs[1][idxs_oi])
-
- if y01 - y00 < 20:
- y01 = y00 + 20
- if y11 - y10 < 20:
- y11 = y10 + 20
- freq_span1 = (y01) - (y00)
- freq_span2 = (y11) - (y10)
-
- yspan = freq_span1 if freq_span1 > freq_span2 else freq_span2
-
- ax[1].plot(times[idxs_oi] - time_oi, fish_freqs[0][idxs_oi], marker='.', markersize=4, color='darkorange', lw=2, alpha=0.4)
- ax[2].plot(times[idxs_oi] - time_oi, fish_freqs[1][idxs_oi], marker='.', markersize=4,color='forestgreen', lw=2, alpha=0.4)
- ax[1].plot([0, 0], [y00 - yspan * 0.2, y00 + yspan * 1.3], '--', color='k')
- ax[2].plot([0, 0], [y10 - yspan * 0.2, y10 + yspan * 1.3], '--', color='k')
-
- ax[1].set_xticks([-30, -15, 0, 15, 30])
- ax[2].set_xticks([-30, -15, 0, 15, 30])
- plt.setp(ax[1].get_xticklabels(), visible=False)
-
- # spectrograms
- f_mask1 = np.arange(len(fill_freqs))[(fill_freqs >= y00 - yspan * 0.2) & (fill_freqs <= y00 + yspan * 1.3)]
- f_mask2 = np.arange(len(fill_freqs))[(fill_freqs >= y10 - yspan * 0.2) & (fill_freqs <= y10 + yspan * 1.3)]
- t_mask = np.arange(len(fill_times))[(fill_times >= time_oi-dt*4) & (fill_times <= time_oi+dt*4)]
-
- ax[1].imshow(decibel(fill_spec[f_mask1[0]:f_mask1[-1], t_mask[0]:t_mask[-1]][::-1]),
- extent=[-dt*4, dt*4, y00 - yspan * 0.2, y00 + yspan * 1.3],
- aspect='auto',vmin = -100, vmax = -50, alpha=0.7, cmap='jet', interpolation='gaussian')
- ax[2].imshow(decibel(fill_spec[f_mask2[0]:f_mask2[-1], t_mask[0]:t_mask[-1]][::-1]),
- extent=[-dt*4, dt*4, y10 - yspan * 0.2, y10 + yspan * 1.3],
- aspect='auto',vmin = -100, vmax = -50, alpha=0.7, cmap='jet', interpolation='gaussian')
-
- ax[1].set_ylim(y00 - yspan * 0.1, y00 + yspan * 1.2)
- ax[1].set_xlim(-dt*3, dt*3)
- ax[2].set_ylim(y10 - yspan * 0.1, y10 + yspan * 1.2)
- ax[2].set_xlim(-dt*3, dt*3)
-
- ax[0].set_xticks([])
- ax[0].set_yticks([])
-
- ax[1].tick_params(labelsize=12)
- ax[2].tick_params(labelsize=12)
-
- ax[2].set_xlabel('time [s]', fontsize=14)
- fig.text(0.02, 0.5, 'frequency [Hz]', fontsize=14, va='center', rotation='vertical')
-
- # plt.ion()
- for i in tqdm(np.arange(len(frames_oi))):
- # break
- video.set(cv2.CAP_PROP_POS_FRAMES, int(frames_oi[i]))
- ret, frame = video.read()
-
- if i == 250:
- dot, = ax[0].plot(0.05, 0.95, 'o', color='firebrick', transform = ax[0].transAxes, markersize=20)
- if i == 280:
- dot.remove()
-
- if i == 0:
- img = ax[0].imshow(frame)
- line1, = ax[1].plot([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
- [y00 - yspan * 0.15, y00 + yspan * 1.3],
- color='k', lw=1)
- line2, = ax[2].plot([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
- [y10 - yspan * 0.15, y10 + yspan * 1.3],
- color='k', lw=1)
- else:
- img.set_data(frame)
- line1.set_data([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
- [y00 - yspan * 0.15, y00 + yspan * 1.3])
- line2.set_data([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
- [y10 - yspan * 0.15, y10 + yspan * 1.3])
-
- label = (os.path.join(create_video_path, 'frame%4.f.jpg' % len(glob.glob(os.path.join(create_video_path, '*.jpg'))))).replace(' ', '0')
- plt.savefig(label, dpi=300)
- # plt.pause(0.001)
+
+ for rise_time in rise_bboxes['t0'][rise_bboxes['id'] == lose_id].to_numpy():
+ relevant_chirps = chirp_times[((chirp_times - rise_time) > 0 ) &
+ ((chirp_times - rise_time) < dt * 3)]
+ if len(relevant_chirps) == 0:
+ continue
+
+ rel_chirp_time = relevant_chirps - rise_time
+
+ HH = int((rise_time / 3600) // 1)
+ MM = int((rise_time - HH * 3600) // 60)
+ SS = int(rise_time - HH * 3600 - MM * 60)
+
+ frames_oi = np.arange(len(frame_times))[((frame_times - rise_time) >= -dt) & ((frame_times - rise_time) <= 3*dt)]
+ idxs_oi = np.arange(len(times))[((times - rise_time) >= -dt) & ((times - rise_time) <= 3*dt)]
+
+ fig = plt.figure(figsize=(16 * 2 / 2.54, 9 * 2 / 2.54))
+ fig.patch.set_facecolor('black')
+ gs = gridspec.GridSpec(6, 2, left=0.075, bottom=0.05, right=.99, top=0.95, width_ratios=(1.5, 3), hspace=.3,
+ wspace=0.05)
+ ax = []
+ ax.append(fig.add_subplot(gs[:, 1]))
+ ax.append(fig.add_subplot(gs[1:3, 0]))
+ ax.append(fig.add_subplot(gs[3:5, 0]))
+
+ y00, y01 = np.nanmin(fish_freqs[0][idxs_oi]), np.nanmax(fish_freqs[0][idxs_oi])
+ y10, y11 = np.nanmin(fish_freqs[1][idxs_oi]), np.nanmax(fish_freqs[1][idxs_oi])
+
+ if y01 - y00 < 20:
+ y01 = y00 + 20
+ if y11 - y10 < 20:
+ y11 = y10 + 20
+ freq_span1 = (y01) - (y00)
+ freq_span2 = (y11) - (y10)
+ yspan = freq_span1 if freq_span1 > freq_span2 else freq_span2
+
+ ax[1].plot(times[idxs_oi] - rise_time, fish_freqs[0][idxs_oi], marker='.', markersize=4, color='darkorange', lw=2,
+ alpha=0.4)
+ ax[2].plot(times[idxs_oi] - rise_time, fish_freqs[1][idxs_oi], marker='.', markersize=4, color='forestgreen',
+ lw=2, alpha=0.4)
+ ax[1].plot([0, 0], [y00 - yspan * 0.2, y00 + yspan * 1.3], '--', color='white')
+ ax[2].plot([0, 0], [y10 - yspan * 0.2, y10 + yspan * 1.3], '--', color='white')
+
+ for ct in rel_chirp_time:
+ ax[2].plot([ct, ct], [y10 - yspan * 0.2, y10 + yspan * 1.3], '--', color='tab:orange')
+
+ ax[1].set_xticks([-30, -15, 0, 15, 30])
+ ax[2].set_xticks([-30, -15, 0, 15, 30])
+ plt.setp(ax[1].get_xticklabels(), visible=False)
+
+ # spectrograms
+ f_mask1 = np.arange(len(fill_freqs))[(fill_freqs >= y00 - yspan * 0.2) & (fill_freqs <= y00 + yspan * 1.3)]
+ f_mask2 = np.arange(len(fill_freqs))[(fill_freqs >= y10 - yspan * 0.2) & (fill_freqs <= y10 + yspan * 1.3)]
+ t_mask = np.arange(len(fill_times))[(fill_times >= rise_time - dt * 4) & (fill_times <= rise_time + dt * 4)]
+
+ ax[1].imshow(decibel(fill_spec[f_mask1[0]:f_mask1[-1], t_mask[0]:t_mask[-1]][::-1]),
+ extent=[-dt * 4, dt * 4, y00 - yspan * 0.2, y00 + yspan * 1.3],
+ aspect='auto', vmin=-100, vmax=-50, cmap='afmhot', interpolation='gaussian')
+ ax[2].imshow(decibel(fill_spec[f_mask2[0]:f_mask2[-1], t_mask[0]:t_mask[-1]][::-1]),
+ extent=[-dt * 4, dt * 4, y10 - yspan * 0.2, y10 + yspan * 1.3],
+ aspect='auto', vmin=-100, vmax=-50, cmap='afmhot', interpolation='gaussian')
+
+ ax[1].set_ylim(y00 - yspan * 0.1, y00 + yspan * 1.2)
+ # ax[1].set_xlim(-dt * 3, dt * 3)
+ ax[1].set_xlim(-dt, dt * 3)
+ ax[2].set_ylim(y10 - yspan * 0.1, y10 + yspan * 1.2)
+ # ax[2].set_xlim(-dt * 3, dt * 3)
+ ax[2].set_xlim(-dt, dt * 3)
+
+ ax[0].set_xticks([])
+ ax[0].set_yticks([])
+
+ ax[1].tick_params(labelsize=12, color='white', labelcolor='white')
+ ax[2].tick_params(labelsize=12, color='white', labelcolor='white')
+
+ # embed()
+ # quit()
+ for a in ax[1:]:
+ a.spines['left'].set_edgecolor('white')
+ a.spines['bottom'].set_edgecolor('white')
+ # for spine in ax[1].spines.values():
+ # spine.set_edgecolor('white')
+ # for spine in ax[2].spines.values():
+ # spine.set_edgecolor('white')
+
+ ax[2].set_xlabel('time [s]', fontsize=14, color='white')
+ fig.text(0.02, 0.5, 'frequency [Hz]', fontsize=14, va='center', rotation='vertical', color='white')
+ # embed()
+ # quit()
+ rise_dot_counter = 0
+ rise_passed = False
+ chirp_dot_counter = np.zeros(len(relevant_chirps), dtype=int)
+ chirp_passed = np.zeros(len(relevant_chirps), dtype=bool)
+ chirp_dot_handls = []
+ chirp_active = False
+
+ # plt.show()
+
+ # embed()
+ # quit()
+ for i in tqdm(np.arange(len(frames_oi))):
+ # break
+ video.set(cv2.CAP_PROP_POS_FRAMES, int(frames_oi[i]))
+ ret, frame = video.read()
+
+ if i == 0:
+ img = ax[0].imshow(frame)
+ line1, = ax[1].plot([frame_times[frames_oi[i]] - rise_time, frame_times[frames_oi[i]] - rise_time],
+ [y00 - yspan * 0.15, y00 + yspan * 1.3],
+ color='white', lw=1)
+ line2, = ax[2].plot([frame_times[frames_oi[i]] - rise_time, frame_times[frames_oi[i]] - rise_time],
+ [y10 - yspan * 0.15, y10 + yspan * 1.3],
+ color='white', lw=1)
+ else:
+ img.set_data(frame)
+ line1.set_data([frame_times[frames_oi[i]] - rise_time, frame_times[frames_oi[i]] - rise_time],
+ [y00 - yspan * 0.15, y00 + yspan * 1.3])
+ line2.set_data([frame_times[frames_oi[i]] - rise_time, frame_times[frames_oi[i]] - rise_time],
+ [y10 - yspan * 0.15, y10 + yspan * 1.3])
+
+ if frame_times[frames_oi[i]] - rise_time > 0:
+ if rise_passed == False:
+ rise_dot, = ax[0].plot(0.05, 0.95, 'o', color='white', transform=ax[0].transAxes, markersize=20)
+ rise_passed = True
+ for pos in ['left', 'bottom', 'right', 'top']:
+ ax[0].spines[pos].set_edgecolor('white')
+ ax[0].spines[pos].set_edgecolor('white')
+
+ if rise_passed == True:
+ if rise_dot_counter < 6:
+ rise_dot_counter += 1
+ elif rise_dot_counter == 6:
+ rise_dot.remove()
+ if not chirp_active:
+ for pos in ['left', 'bottom', 'right', 'top']:
+ ax[0].spines[pos].set_edgecolor('k')
+ ax[0].spines[pos].set_edgecolor('k')
+
+ rise_dot_counter += 1
+ else:
+ pass
+
+ for enu, chirp_time in enumerate(relevant_chirps):
+ if frame_times[frames_oi[i]] - chirp_time > 0:
+ if chirp_passed[enu] == False:
+ chirp_dot, = ax[0].plot(0.05, 0.95, 'o', color='tab:orange', transform=ax[0].transAxes,
+ markersize=20)
+ chirp_dot_handls.append(chirp_dot)
+ for pos in ['left', 'bottom', 'right', 'top']:
+ ax[0].spines[pos].set_edgecolor('tab:orange')
+ ax[0].spines[pos].set_edgecolor('tab:orange')
+ chirp_passed[enu] = True
+
+ chirp_active = True
+ if chirp_passed[enu] == True:
+ if chirp_dot_counter[enu] < 6:
+ chirp_dot_counter[enu] += 1
+ elif chirp_dot_counter[enu] == 6:
+ chirp_dot_handls[enu].remove()
+ for pos in ['left', 'bottom', 'right', 'top']:
+ ax[0].spines[pos].set_edgecolor('k')
+ ax[0].spines[pos].set_edgecolor('k')
+ chirp_dot_counter[enu] += 1
+ else:
+ pass
+
+ label = (os.path.join(create_video_path,
+ 'frame%4.f.jpg' % len(glob.glob(os.path.join(create_video_path, '*.jpg'))))).replace(' ',
+ '0')
+ plt.savefig(label, dpi=300)
+
+
+ # for fish_nr in np.arange(2)[::-1]:
+ # for idx_oi in tqdm(np.array(rise_idx[fish_nr][~np.isnan(rise_idx[fish_nr])], dtype=int)):
+ # time_oi = times[idx_oi]
+ #
+ # HH = int((time_oi / 3600) // 1)
+ # MM = int((time_oi - HH * 3600) // 60)
+ # SS = int(time_oi - HH * 3600 - MM * 60)
+ #
+ # frames_oi = np.arange(len(frame_times))[np.abs(frame_times - time_oi) <= dt]
+ # idxs_oi = np.arange(len(times))[np.abs(times - time_oi) <= dt*3]
+ #
+ # fig = plt.figure(figsize=(16*2/2.54, 9*2/2.54))
+ # gs = gridspec.GridSpec(6, 2, left=0.075, bottom=0.05, right=1, top=0.95, width_ratios=(1.5, 3), hspace=.3, wspace=0.05)
+ # ax = []
+ # ax.append(fig.add_subplot(gs[:, 1]))
+ # ax.append(fig.add_subplot(gs[1:3, 0]))
+ # ax.append(fig.add_subplot(gs[3:5, 0]))
+ #
+ #
+ # y00, y01 = np.nanmin(fish_freqs[0][idxs_oi]), np.nanmax(fish_freqs[0][idxs_oi])
+ # y10, y11 = np.nanmin(fish_freqs[1][idxs_oi]), np.nanmax(fish_freqs[1][idxs_oi])
+ #
+ # if y01 - y00 < 20:
+ # y01 = y00 + 20
+ # if y11 - y10 < 20:
+ # y11 = y10 + 20
+ # freq_span1 = (y01) - (y00)
+ # freq_span2 = (y11) - (y10)
+ #
+ # yspan = freq_span1 if freq_span1 > freq_span2 else freq_span2
+ #
+ # ax[1].plot(times[idxs_oi] - time_oi, fish_freqs[0][idxs_oi], marker='.', markersize=4, color='darkorange', lw=2, alpha=0.4)
+ # ax[2].plot(times[idxs_oi] - time_oi, fish_freqs[1][idxs_oi], marker='.', markersize=4,color='forestgreen', lw=2, alpha=0.4)
+ # ax[1].plot([0, 0], [y00 - yspan * 0.2, y00 + yspan * 1.3], '--', color='k')
+ # ax[2].plot([0, 0], [y10 - yspan * 0.2, y10 + yspan * 1.3], '--', color='k')
+ #
+ # ax[1].set_xticks([-30, -15, 0, 15, 30])
+ # ax[2].set_xticks([-30, -15, 0, 15, 30])
+ # plt.setp(ax[1].get_xticklabels(), visible=False)
+ #
+ # # spectrograms
+ # f_mask1 = np.arange(len(fill_freqs))[(fill_freqs >= y00 - yspan * 0.2) & (fill_freqs <= y00 + yspan * 1.3)]
+ # f_mask2 = np.arange(len(fill_freqs))[(fill_freqs >= y10 - yspan * 0.2) & (fill_freqs <= y10 + yspan * 1.3)]
+ # t_mask = np.arange(len(fill_times))[(fill_times >= time_oi-dt*4) & (fill_times <= time_oi+dt*4)]
+ #
+ # ax[1].imshow(decibel(fill_spec[f_mask1[0]:f_mask1[-1], t_mask[0]:t_mask[-1]][::-1]),
+ # extent=[-dt*4, dt*4, y00 - yspan * 0.2, y00 + yspan * 1.3],
+ # aspect='auto',vmin = -100, vmax = -50, alpha=0.7, cmap='jet', interpolation='gaussian')
+ # ax[2].imshow(decibel(fill_spec[f_mask2[0]:f_mask2[-1], t_mask[0]:t_mask[-1]][::-1]),
+ # extent=[-dt*4, dt*4, y10 - yspan * 0.2, y10 + yspan * 1.3],
+ # aspect='auto',vmin = -100, vmax = -50, alpha=0.7, cmap='jet', interpolation='gaussian')
+ #
+ # ax[1].set_ylim(y00 - yspan * 0.1, y00 + yspan * 1.2)
+ # ax[1].set_xlim(-dt*3, dt*3)
+ # ax[2].set_ylim(y10 - yspan * 0.1, y10 + yspan * 1.2)
+ # ax[2].set_xlim(-dt*3, dt*3)
+ #
+ # ax[0].set_xticks([])
+ # ax[0].set_yticks([])
+ #
+ # ax[1].tick_params(labelsize=12)
+ # ax[2].tick_params(labelsize=12)
+ #
+ # ax[2].set_xlabel('time [s]', fontsize=14)
+ # fig.text(0.02, 0.5, 'frequency [Hz]', fontsize=14, va='center', rotation='vertical')
+ #
+ # # plt.ion()
+ # for i in tqdm(np.arange(len(frames_oi))):
+ # # break
+ # video.set(cv2.CAP_PROP_POS_FRAMES, int(frames_oi[i]))
+ # ret, frame = video.read()
+ #
+ # if i == 250:
+ # dot, = ax[0].plot(0.05, 0.95, 'o', color='firebrick', transform = ax[0].transAxes, markersize=20)
+ # if i == 280:
+ # dot.remove()
+ #
+ # if i == 0:
+ # img = ax[0].imshow(frame)
+ # line1, = ax[1].plot([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
+ # [y00 - yspan * 0.15, y00 + yspan * 1.3],
+ # color='k', lw=1)
+ # line2, = ax[2].plot([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
+ # [y10 - yspan * 0.15, y10 + yspan * 1.3],
+ # color='k', lw=1)
+ # else:
+ # img.set_data(frame)
+ # line1.set_data([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
+ # [y00 - yspan * 0.15, y00 + yspan * 1.3])
+ # line2.set_data([frame_times[frames_oi[i]] - time_oi, frame_times[frames_oi[i]] - time_oi],
+ # [y10 - yspan * 0.15, y10 + yspan * 1.3])
+ #
+ # label = (os.path.join(create_video_path, 'frame%4.f.jpg' % len(glob.glob(os.path.join(create_video_path, '*.jpg'))))).replace(' ', '0')
+ # plt.savefig(label, dpi=300)
+ # # plt.pause(0.001)
# quit()
- win_lose_str = 'lose' if fish_nr == 1 else 'win'
- # video_name = ("./rise_video/%s_%2.f:%2.f:%2.f.mp4" % (win_lose_str, HH, MM, SS)).replace(' ', '0')
- # command = "ffmpeg -r 25 -i './rise_video/frame%4d.jpg' -vf 'pad=ceil(iw/2)*2:ceil(ih/2)*2' -vcodec libx264 -y -an"
-
- video_name = os.path.join(create_video_path, ("%s_%2.f:%2.f:%2.f.mp4" % (win_lose_str, HH, MM, SS)).replace(' ', '0'))
- command1 = "ffmpeg -r 25 -i"
- frames_path = '"%s"' % os.path.join(create_video_path, "frame%4d.jpg")
- command2 = "-vf 'pad=ceil(iw/2)*2:ceil(ih/2)*2' -vcodec libx264 -y -an"
-
- os.system(' '.join([command1, frames_path, command2, video_name]))
- os.system(' '.join(['rm', os.path.join(create_video_path, '*.jpg')]))
- # os.system(' '.join([command, video_name]))
- # os.system('rm ./rise_video/*.jpg')
- plt.close()
+ win_lose_str = 'lose'
+ # video_name = ("./rise_video/%s_%2.f:%2.f:%2.f.mp4" % (win_lose_str, HH, MM, SS)).replace(' ', '0')
+ # command = "ffmpeg -r 25 -i './rise_video/frame%4d.jpg' -vf 'pad=ceil(iw/2)*2:ceil(ih/2)*2' -vcodec libx264 -y -an"
+
+ video_name = os.path.join(create_video_path, ("%s_%2.f:%2.f:%2.f.mp4" % (win_lose_str, HH, MM, SS)).replace(' ', '0'))
+ command1 = "ffmpeg -r 25 -i"
+ frames_path = '"%s"' % os.path.join(create_video_path, "frame%4d.jpg")
+ command2 = "-vf 'pad=ceil(iw/2)*2:ceil(ih/2)*2' -vcodec libx264 -y -an"
+
+ os.system(' '.join([command1, frames_path, command2, video_name]))
+ os.system(' '.join(['rm', os.path.join(create_video_path, '*.jpg')]))
+ # os.system(' '.join([command, video_name]))
+ # os.system('rm ./rise_video/*.jpg')
+ plt.close()
embed()
quit()