travail d'un we (j'en ai big marre)

.cache

@@ -1 +0,0 @@
-{"access_token": "BQDeVV_yylewo72n9ZtSMTn1WNhJKSbUBDKv18Cl-QY7dphidwC9jDuGuZWKaIWZv-fVIG1uuP1XvJFKwcj3GOxgRxYJbaWOLtogCHkAxC-iOaZe6uphn-vCy5rbX6Xlx9XVUG-jHNu0jaCf1-ueTRUQuyF0Btu4_aAcIktTnYyofSUJuk_Mdi1J6V3hmARkCl34Rv-4hgfXcIqQ_rpdCFHGheEU1rSL5oME", "token_type": "Bearer", "expires_in": 3600, "scope": "user-modify-playback-state user-read-playback-state", "expires_at": 1757966041, "refresh_token": "AQAxD3wm_8aDlK9w2ZsibKsrPY0SxUJb2UaqiT2ygxK-pEq2ojxPzgLa6DNt9EpP3mjFDCLmGO5glj5fSpR3ZnqEa26belG4EQv5FOeee38ix31o2xuxPbDsY44KR5Uj1KE"}

final-loop/Dockerfile

@@ -0,0 +1,10 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+COPY requirements.txt ./
+
+RUN pip install --no-cache-dir -r requirements.txt
+
+COPY src/ . 
+

final-loop/client-cache/credentials.json

@@ -0,0 +1 @@
+{"username":"mathias-120","auth_type":1,"auth_data":"QWdDZF9iOVZDTUltQ0Noc0lnSFdfNU5QOXBMdFdiQllFclJ3dHM3ZVRaY1lzUEpKd1Jwc1pOc3FzdjFwYnRYZ2ZRSXE2Q1ZiWTBjdzRDTUYzdkJMekdqOVliRTh1UldlZlJOdF94eEgydzJUWmhtT0RlX295ODdrTzZDYXFuMW5SVEQ4TV95S2R0aEJLTDZldkxPeDlva0wtcHJNY0p6Q3VzQl9YOGFhVHNYaw=="}

final-loop/client-cache/volume

@@ -0,0 +1 @@
+65535

final-loop/compose.yml

@@ -0,0 +1,34 @@
+services:
+  librespot:
+    container_name: spotvinyl-client
+    image: giof71/librespot:latest
+    network_mode: host
+    devices:
+      - /dev/snd:/dev/snd
+    environment:
+      - DEVICE=hw:x20,0
+      - BACKEND=alsa
+      - BITRATE=320
+      - INITIAL_VOLUME=100
+      - DEVICE_NAME=spotvinyl
+      - ENABLE_OAUTH=headless       # Enables OAuth headless mode
+      - ENABLE_SYSTEM_CACHE=Y       # Cache token for persistent login
+    volumes:
+      - ./client-cache:/data/system-cache
+    stdin_open: true
+    tty: true
+
+  spotvinyl:
+      build: .
+      container_name: spotvinyl
+      devices:
+        - /dev/video2
+      volumes:
+        - ./src:/app
+        # - ./spotvinyl-cache
+      working_dir: /app
+      env_file:
+      - .env
+      command: python3 decode_barcode.py
+      ports:
+        - "5000:5000"

final-loop/requirements.txt

@@ -0,0 +1,32 @@
+certifi==2025.11.12
+chardet==5.2.0
+charset-normalizer==3.4.4
+contourpy==1.3.3
+crccheck==1.3.1
+cycler==0.12.1
+decorator==5.2.1
+fonttools==4.60.1
+idna==3.11
+ImageIO==2.37.2
+joblib==1.5.2
+kiwisolver==1.4.9
+lazy_loader==0.4
+matplotlib==3.10.7
+networkx==3.5
+numpy==2.2.6
+opencv-python==4.12.0.88
+packaging==25.0
+pillow==12.0.0
+pyparsing==3.2.5
+python-dateutil==2.9.0.post0
+PyWavelets==1.9.0
+redis==7.1.0
+requests==2.32.5
+scikit-image==0.25.2
+scikit-learn==1.7.2
+scipy==1.16.3
+six==1.17.0
+spotipy==2.25.1
+threadpoolctl==3.6.0
+tifffile==2025.10.16
+urllib3==2.5.0

final-loop/spotify-codes-part-2/.cache

@@ -1 +0,0 @@
-{"access_token": "BQAHRFXWQMMKWNbUO3sfhk92iUGi5VJNZmB2lTjRim-g2AIe88mgDvyc1NywjCVBTeZK-b3PkXzGDANJDDOouitEt5P8z0jpVuPrpalwAg0PzEwtKBXr8PHvacajO9B3s7Wy0s7G3CFlfGfbOfmXtW_vF8G2_ooGnlFp_oM8RcOyBl7D5Okf6kr07CWIJty4mNeTf1Ifd212u1tBnbU64lckqlQ0f0W105mt", "token_type": "Bearer", "expires_in": 3600, "refresh_token": "AQCSe9ARCDB-Q6gzna_KKAlcEuNOx2IC9BSVXS5GZxNDi4AjJdA4Kn3hp1YPfiPfogd2rz-5zLbyjUxiRj9oTd-q5EItEPZHIVt-eMf7gCGHfj6h-hLpRrnhgMZjzRAS7CY", "scope": "user-modify-playback-state user-read-playback-state", "expires_at": 1757966002}

final-loop/spotify-codes-part-2/requirements.txt

@@ -1,21 +0,0 @@
-certifi>=2023.5.7
-chardet>=5.1.0
-crccheck>=1.0
-cycler>=0.11.0
-decorator>=5.1.1
-idna>=3.5
-imageio>=2.31.1
-kiwisolver>=1.4.4
-matplotlib>=3.7.1
-networkx>=3.1
-numpy>=1.24.2
-Pillow>=10.0.0
-pyparsing>=3.0.9
-python-dateutil>=2.8.2
-PyWavelets>=1.4.1
-requests>=2.31.0
-scikit-image>=0.25.2
-scipy>=1.11.1
-six>=1.16.0
-tifffile>=2023.7.23
-urllib3>=2.0.4

final-loop/spotify-codes-part-2/src/decode_barcode.py

@@ -1,57 +0,0 @@
-import argparse
-import pprint
-from get_heights import get_heights
-from encode_decode import spotify_bar_decode
-from get_uri import get_uri, get_info
-import cv2
-
-
-def process_frame(frame, token):
-    heights = get_heights(frame)
-    print(len(heights))  # assumes get_heights can take image array
-    if len(heights) != 23:
-        return None  # skip bad frames
-    else:
-        print("ON TROUVE UN CODE")
-
-    heights = heights[1:11] + heights[12:-1]
-    decoded = spotify_bar_decode(heights)
-    uri = get_uri(decoded, token)
-    summary, full_response = get_info(uri["target"], token)
-    return summary
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--token", required=True)
-    args = parser.parse_args()
-    token = args.token
-
-    cap = cv2.VideoCapture(0)  # 0 for default webcam
-
-    while True:
-        ret, frame = cap.read()
-        if not ret:
-            break
-
-        # Définir les dimensions et la marge du cadre
-        height, width, _ = frame.shape
-        margin = 100  # ajustez la taille du cadre ici
-        frame = frame[margin:height - margin, margin:width - margin]
-
-        try:
-            summary = process_frame(frame, token)
-        except Exception:
-            continue
-
-        if summary:
-            print("Summary:")
-            pprint.pprint(summary)
-
-        cv2.imshow("Live Barcode", frame)
-
-        if cv2.waitKey(1) & 0xFF == ord('q'):
-            break
-
-    cap.release()
-    cv2.destroyAllWindows()

final-loop/src/decode_barcode.py

@@ -0,0 +1,86 @@
+import argparse
+import pprint
+from get_heights import get_heights
+from encode_decode import spotify_bar_decode
+from get_uri import get_uri, get_info
+import cv2
+from start_song import start_song
+import os
+from flask import Flask, Response
+import threading
+import time
+import numpy as np
+
+os.environ["QT_QPA_PLATFORM"] = "xcb"
+def process_frame(frame, token):
+    
+    heights,preprocess = get_heights(frame)
+    cv2.imshow("frame",  preprocess)
+    if len(heights)!=23:
+        return None  # skip bad frames
+    else:
+        print("ON TROUVE UN CODE")
+
+
+    heights = heights[1:11] + heights[12:-1]
+    decoded = spotify_bar_decode(heights)
+    uri = get_uri(decoded, token)
+    summary, full_response = get_info(uri["target"], token)
+    print(f"SONG FOUND : {summary["name"]}")
+    if uri:
+        start_song(uri['target'],os.getenv('DEVICE_ID'))
+    return summary
+
+
+
+
+
+
+
+
+
+
+if __name__ == "__main__":
+
+
+
+    cap = cv2.VideoCapture('/dev/video0')
+
+
+    token = os.getenv('ACCESS_TOKEN')
+    if not token:
+        token = "BQCph85n2Cr-h8jKWhsdsdhywaX3h_bn4pJ_-jdque2u_gn9bI-OdthIowGSU6r058QozL0eJfzy_ClWezXYKrQO2npuyfWVphxSQrKqhBWkGr5bK0UrIfsKKAdJvoNrXD9Db-ObgP5D3-rMpF0Xq3RXwMpTal9NpzTJcHZs_PBjbNClJVy24Jk5WfGbKZPkMs_Hon5TjABx4QzxzE2vxjd4X4EyPlyPuKiIVp-f7yTSJbbRLqt-_O_VJ9mnQ1RgGK16afY7p3JZH_B6-VSCrFuhK_m9yhSieiWoqEeopFEX47Nc4-tuqe8CXcYGiRLZBIcc4w64ly36ZIftxRN7ehcJb2gcV26ZqMS1lg1Yxp0OD4ShJJsinA69X535_w"
+    print(token)
+
+
+    if not cap.isOpened():
+        print("Error: Could not open camera.")
+        exit(1)
+    else:
+        print("Camera is working and ready to capture frames.")
+
+    while True:
+        ret, frame = cap.read()
+        if not ret:
+            break
+        # Crop same as streaming for consistency
+        height, width, _ = frame.shape
+        margin = 100
+        frame = frame[margin:height - margin, margin:width - margin]
+
+        try:
+            
+
+            summary = process_frame(frame, token)
+
+        except Exception as e:
+            print(e)
+            print("")
+            continue
+        # cv2.imshow("preframe", frame)
+
+        if cv2.waitKey(1) & 0xFF == ord('q'):
+            break
+
+    cap.release()
+    cv2.destroyAllWindows()

final-loop/src/get_heights.py

@@ -8,24 +8,46 @@ from skimage.color import rgb2gray
 import matplotlib.patches as patches
 from sklearn.cluster import KMeans
 import warnings
+from skimage.morphology import remove_small_objects
+from skimage.transform import resize
+from skimage import exposure
+from skimage.morphology import erosion, square
+import cv2
+from skimage.filters import threshold_local
+from scipy import ndimage as ndi
+from skimage.segmentation import watershed
+from skimage.morphology import opening, rectangle
+from scipy.ndimage import gaussian_filter
 
 warnings.filterwarnings("ignore", category=FutureWarning, message=".*square.*deprecated.*")
 
-
+#### keep this. If does not work, remove black and reaply the logic only to not-black part of the picture
 def get_heights(image):
     # image = io.imread(filename)
+
+    
     im = rgb2gray(image)
-    binary_im = im > threshold_otsu(im)
+
-    smooth_im = gaussian(binary_im.astype(float), sigma=1)
+    # Filtrage gaussien léger pour diminuer bruit
-    morph_im = closing(smooth_im > 0.5, square(3))
+    im_blur = gaussian_filter(im, sigma=1)
-    labeled = label(morph_im)
+
+    # Calcul du seuil local avec block_size impair, ajuster offset si besoin
+    th = threshold_local(im_blur, block_size=71, offset=-0.09)
+
+    binary_im = im_blur > th
+
+    separated = binary_im
+    labeled = label(separated)
+
     bar_dims = [r.bbox for r in regionprops(labeled)]
     bar_dims.sort(key=lambda x: x[1])  # left to right
     
-    bars = bar_dims[1:]  # skip logo
+    bars = bar_dims#[1:]  # skip logo
     bar_heights_raw = []
     if(len(bars)!=23):
-        return [0]
+        print(len(bars))
+        return  [0], (separated.astype("uint8") * 255)  # convert to 0/255 uint8
+    
     for bar in bars:
         top, left, bottom, right = bar
         effective_height = bottom - top  # use bounding box height directly
@@ -44,5 +66,5 @@ def get_heights(image):
         closest_cluster = np.argmin(diffs)
         predicted_levels.append(int(closest_cluster))
     
-
+    print(predicted_levels)
-    return predicted_levels
+    return predicted_levels, (separated.astype("uint8") * 255)

final-loop/src/start_song.py

@@ -9,7 +9,7 @@ REDIRECT_URI = 'https://vinyly.couraud.xyz'
 SCOPE = 'user-modify-playback-state user-read-playback-state'
 
 
-def main():
+def start_song(URI="spotify:track:0RoA7ObU6phWpqhlC9zH4Z",device_id="a499b8f3684d8098ffb5f9ff11392ebdd61fc6d1"):
     auth_manager = SpotifyOAuth(client_id=CLIENT_ID,
                                 client_secret=CLIENT_SECRET,
                                 redirect_uri=REDIRECT_URI,
@@ -26,28 +26,18 @@ def main():
 
     sp = spotipy.Spotify(auth_manager=auth_manager)
 
-    if len(sys.argv) < 2:
-        print('Usage: python play_spotify.py "song name"')
-        sys.exit(1)
-
-    song_name = ' '.join(sys.argv[1:])
-
-    results = sp.search(q=song_name, type='track', limit=1)
-    if not results['tracks']['items']:
-        print(f'No track found for: {song_name}')
-        sys.exit(1)
-
-    track_uri = results['tracks']['items'][0]['uri']
 
     devices = sp.devices()
     if not devices['devices']:
         print('No active Spotify devices found. Please start playback on a device.')
         sys.exit(1)
 
-    active_device_id = devices['devices'][0]['id']
+    current = sp.current_user_playing_track()
-
+    if current and current.get("item"):
-    sp.start_playback(device_id=active_device_id, uris=[track_uri])
+        current_uri = current["item"]["uri"]
-    print(f'Playing "{song_name}" on device ID: {active_device_id}')
+        
+    if current_uri != URI:
+        sp.start_playback(device_id=device_id, uris=[URI])
 
 if __name__ == '__main__':
-    main()
+    start_song(URI,device_id)

old/.cache

@@ -0,0 +1 @@
+{"access_token": "BQBR3Dnu7QMSOnq8G_8lOiz858WKJmMxiCgskqjp3QDu17EcQWx3Y8ALVQGSXzUcTgkJb-z5oHjJxEQJNfz8tSYREfJGGMKQfoCo0P2tCUbnB0wdGm7iSmWOlYuvrnDTVleJ9nJBGG6vVGc2ZEIl43T54_TmKbkPzampV8FuuGIATUvzbjRO6uEHqzc3ImuBELCZJjj0n8-h4zImXifkJP6pssEY76_GWgKo_HVx", "token_type": "Bearer", "expires_in": 3600, "scope": "user-modify-playback-state user-read-playback-state", "expires_at": 1763737778, "refresh_token": "AQAxD3wm_8aDlK9w2ZsibKsrPY0SxUJb2UaqiT2ygxK-pEq2ojxPzgLa6DNt9EpP3mjFDCLmGO5glj5fSpR3ZnqEa26belG4EQv5FOeee38ix31o2xuxPbDsY44KR5Uj1KE"}

old/spotify-codes-part-2/src/get_heights.py

@@ -21,12 +21,12 @@ def get_heights(filename: str):
     
     bars = bar_dims[1:]  # skip logo
     bar_heights_raw = []
-    
+    print(len(bars))
     for bar in bars:
         top, left, bottom, right = bar
         effective_height = bottom - top  # use bounding box height directly
         bar_heights_raw.append(effective_height)
-    print(len(bars))
+
     # Cluster measured heights to 8 clusters representing discrete bar levels
     bar_heights_raw_np = np.array(bar_heights_raw).reshape(-1, 1)
     
@@ -38,8 +38,8 @@ def get_heights(filename: str):
     for h in bar_heights_raw:
         diffs = np.abs(cluster_centers - h)
         closest_cluster = np.argmin(diffs)
-        predicted_levels.append(closest_cluster)
+        predicted_levels.append(int(closest_cluster))
     
 
-    print(len(predicted_levels))
+    print((predicted_levels))
     return predicted_levels