Spaces:
Sleeping
Sleeping
Muhammad Waqas
commited on
Commit
·
2e40bb4
1
Parent(s):
2677214
Added: Generate image to video
Browse files- app.py +168 -96
- requirements.txt +1 -0
- workflows/cogvideox_image_to_video_workflow_api.json +3 -3
app.py
CHANGED
@@ -6,6 +6,7 @@ import random
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import urllib.request
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import urllib.parse
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import websocket
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import uuid
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from dotenv import load_dotenv
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from flask import Flask, request, jsonify, render_template, send_file
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@@ -27,44 +28,8 @@ ws_address = os.getenv("WS_ADDRESS")
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# Generate a unique client ID
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client_id = str(uuid.uuid4())
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def allowed_file(filename):
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"""Check if the uploaded file has an allowed extension."""
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return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
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def save_base64_image(b64_string):
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"""Decode a base64 string and save it as an image."""
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header, encoded = b64_string.split(',', 1) # Handle data URI schemes if provided
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image_data = base64.b64decode(encoded)
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# Determine image extension from data URI or use a default one
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ext = header.split('/')[1].split(';')[0] if '/' in header else 'png'
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image_path = f"/tmp/{uuid.uuid4()}.{ext}"
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with open(image_path, 'wb') as f:
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f.write(image_data)
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return image_path
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def make_request(url, data=None, headers=None):
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req = urllib.request.Request(url, data=data, headers=headers)
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try:
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with urllib.request.urlopen(req) as response:
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response_body = response.read().decode() # Decode the response
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# print(response_body)
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return json.loads(response_body) # Convert to JSON if valid
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except urllib.error.HTTPError as e:
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print(f"HTTPError: {e.code}, {e.reason}")
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print(e.read().decode()) # Print detailed error response
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except urllib.error.URLError as e:
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print(f"URLError: {e.reason}")
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def queue_prompt(prompt, token):
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payload = {"prompt": prompt, "client_id": client_id}
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data = json.dumps(payload).encode('utf-8')
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headers = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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return make_request(f"{server_address}/prompt", data=data, headers=headers)
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def get_image(filename, subfolder, image_type, token):
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url_values = {'filename': filename, 'subfolder': subfolder, 'type': image_type}
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@@ -78,15 +43,9 @@ def get_image(filename, subfolder, image_type, token):
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print(e.read())
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raise
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def get_history(prompt_id, token):
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headers = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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return make_request(f"{server_address}/history/{prompt_id}", headers=headers)
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def get_images(ws,
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prompt_id = queue_prompt(
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output_images = {}
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while True:
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@@ -110,6 +69,7 @@ def get_images(ws, prompt, token):
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return output_images
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def fetch_video(video_data, token):
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video_url = f"{server_address}/download?file={video_data['filename']}"
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req = urllib.request.Request(video_url)
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@@ -151,12 +111,12 @@ def generate_image():
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with open(file_path, 'r', encoding='utf-8') as file:
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workflow_jsondata = file.read()
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-
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#
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# seednum = random.randint(1, 9999999999999)
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#
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#######################
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# For model Flux1.dev #
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@@ -164,7 +124,7 @@ def generate_image():
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# Generate a random 15-digit seed as an integer
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seednum = random.randint(100000000000000, 999999999999999)
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-
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ws = websocket.WebSocket()
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@@ -174,7 +134,7 @@ def generate_image():
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except websocket.WebSocketException as e:
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return jsonify({'error': f'WebSocket connection failed: {str(e)}'}), 500
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images = get_images(ws,
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ws.close()
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output_images_base64 = []
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@@ -194,88 +154,200 @@ def generate_image():
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def get_image_file(filename):
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return send_file(filename, mimetype='image/png')
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# Generate image to video route
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@app.route('/image_to_video', methods=['POST'])
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def image_to_video():
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data = request.json
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# Extract
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token = request.headers.get('Authorization')
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if token
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return jsonify({'error': '
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token = token.split(" ")[1]
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# token = base64.b64decode(token).decode("utf-8")
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#
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text_prompt = data
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if not text_prompt:
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return jsonify({'error': 'Text prompt is required'}), 400
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# Handle uploaded image or base64
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image_file = request.files.get('image')
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base64_image = data
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if image_file:
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# Validate and save uploaded image
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if not allowed_file(image_file.filename):
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return jsonify({'error': 'Unsupported image format'}), 400
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filename = secure_filename(image_file.filename)
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image_path = f"/tmp/{uuid.uuid4()}_{filename}"
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image_file.save(image_path)
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elif base64_image:
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# Save base64
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try:
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image_path = save_base64_image(base64_image)
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except Exception as e:
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return jsonify({'error': f'Invalid base64 image data: {str(e)}'}), 400
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else:
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return jsonify({'error': 'Image is required (
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#
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current_dir = os.path.dirname(os.path.abspath(__file__))
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#
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with open(file_path, 'r', encoding='utf-8') as file:
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workflow = json.load(file)
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workflow["30"]["inputs"]["prompt"] = text_prompt # Text prompt
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workflow["36"]["inputs"]["upload"] = image_path # Image path
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workflow["31"]["inputs"]["prompt"] = "Low quality, watermark, strange motion" # Negative prompt
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seed = random.randint(1e14, 9e14)
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workflow["57"]["inputs"]["seed"] = seed # Set reproducibility seed
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# WebSocket connection to trigger workflow
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ws = websocket.WebSocket()
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{"Authorization": f"Bearer {token}"})
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while True:
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message
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if message.get('type') == 'completed':
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video_data = message['data']
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break
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# Fetch
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return send_file(
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io.BytesIO(
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mimetype='video/mp4',
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as_attachment=True,
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download_name='generated_video.mp4'
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)
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=7860) # Removed 'debug=True'
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import urllib.request
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import urllib.parse
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import websocket
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import requests
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import uuid
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from dotenv import load_dotenv
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from flask import Flask, request, jsonify, render_template, send_file
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# Generate a unique client ID
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client_id = str(uuid.uuid4())
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def get_image(filename, subfolder, image_type, token):
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url_values = {'filename': filename, 'subfolder': subfolder, 'type': image_type}
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print(e.read())
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raise
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def get_images(ws, workflow, token):
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prompt_id = queue_prompt(workflow, token)['prompt_id']
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output_images = {}
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while True:
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return output_images
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def fetch_video(video_data, token):
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video_url = f"{server_address}/download?file={video_data['filename']}"
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req = urllib.request.Request(video_url)
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with open(file_path, 'r', encoding='utf-8') as file:
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workflow_jsondata = file.read()
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workflow = json.loads(workflow_jsondata)
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workflow["6"]["inputs"]["text"] = text_prompt
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# workflow["7"]["inputs"]["text"] = "text, watermark, low quality, extra hands, extra legs."
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# seednum = random.randint(1, 9999999999999)
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# workflow["3"]["inputs"]["seed"] = seednum
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#######################
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# For model Flux1.dev #
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# Generate a random 15-digit seed as an integer
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seednum = random.randint(100000000000000, 999999999999999)
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workflow["31"]["inputs"]["seed"] = seednum
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ws = websocket.WebSocket()
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except websocket.WebSocketException as e:
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return jsonify({'error': f'WebSocket connection failed: {str(e)}'}), 500
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images = get_images(ws, workflow, token)
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ws.close()
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output_images_base64 = []
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def get_image_file(filename):
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return send_file(filename, mimetype='image/png')
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def allowed_file(filename):
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"""Check if the uploaded file has an allowed extension."""
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return '.' in filename and filename.rsplit('.', 1)[1].lower() in ALLOWED_EXTENSIONS
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+
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def save_base64_image(b64_string):
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"""Decode a base64 string and save it as an image."""
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try:
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# Handle Data URI scheme if present
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if ',' in b64_string:
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header, encoded = b64_string.split(',', 1)
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ext = header.split('/')[1].split(';')[0] if '/' in header else 'png'
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else:
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encoded = b64_string
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ext = 'png'
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# Decode the image data
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image_data = base64.b64decode(encoded)
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# Generate a unique path for the image
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image_path = f"/tmp/{uuid.uuid4()}.{ext}"
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# Ensure directory exists
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os.makedirs('/tmp/', exist_ok=True)
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# Save the image
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with open(image_path, 'wb') as f:
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f.write(image_data)
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print(f"Image saved at: {image_path}")
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return (f"https://gosign-de-comfyui-api.hf.space{image_path}")
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except Exception as e:
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raise ValueError(f"Failed to save image: {e}")
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def make_request(url, data=None, headers=None):
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req = urllib.request.Request(url, data=data, headers=headers)
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try:
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with urllib.request.urlopen(req) as response:
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response_body = response.read().decode() # Decode the response
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# print(response_body)
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return json.loads(response_body) # Convert to JSON if valid
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except urllib.error.HTTPError as e:
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print(f"HTTPError: {e.code}, {e.reason}")
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print(e.read().decode()) # Print detailed error response
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except urllib.error.URLError as e:
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print(f"URLError: {e.reason}")
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# Helper: Queue the prompt
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def queue_prompt(workflow, token):
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payload = {"prompt": workflow, "client_id": client_id}
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headers = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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response = make_request(f"{server_address}/prompt", data=json.dumps(payload).encode('utf-8'), headers=headers)
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if not response or 'prompt_id' not in response:
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raise ValueError("Failed to queue the prompt. Check the request or API response.")
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return response['prompt_id']
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def get_history(prompt_id, token):
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headers = {
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'Authorization': f'Bearer {token}',
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'Content-Type': 'application/json'
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}
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return make_request(f"{server_address}/history/{prompt_id}", headers=headers)
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def get_video_data(filename, subfolder, token):
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url_values = {'filename': filename, 'subfolder': subfolder}
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url = f"{server_address}/view?{urllib.parse.urlencode(url_values)}"
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req = urllib.request.Request(url)
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req.add_header("Authorization", f"Bearer {token}")
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try:
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return urllib.request.urlopen(req).read() # Return video content
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except urllib.error.HTTPError as e:
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print(f"HTTP Error: {e.code} - {e.reason}")
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print(e.read())
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raise
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# Helper: Upload Image to Hugging Face
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def upload_image_to_hf(image_path, token):
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with open(image_path, 'rb') as img:
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headers = {
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"Authorization": f"Bearer {token}",
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"Content-Type": "image/jpeg" # Change as per your image type
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}
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response = requests.post(
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"https://gosign-de-image-to-video.hf.space",
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headers=headers,
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files={'file': img}
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)
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if response.status_code != 200:
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raise ValueError(f"Failed to upload image: {response.text}")
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return response.json().get('url')
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# Route: Image to Video
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@app.route('/image_to_video', methods=['POST'])
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def image_to_video():
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data = request.json
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# Extract and validate token
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token = request.headers.get('Authorization')
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if not token or not token.startswith("Bearer "):
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return jsonify({'error': 'Valid Bearer token required'}), 400
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token = token.split(" ")[1]
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# Validate text prompt
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text_prompt = data.get('text_prompt')
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if not text_prompt:
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return jsonify({'error': 'Text prompt is required'}), 400
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+
# Handle uploaded image or base64 image
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image_file = request.files.get('image')
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base64_image = data.get('base64_image')
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if image_file:
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+
# Validate and save the uploaded image
|
277 |
if not allowed_file(image_file.filename):
|
278 |
return jsonify({'error': 'Unsupported image format'}), 400
|
279 |
filename = secure_filename(image_file.filename)
|
280 |
image_path = f"/tmp/{uuid.uuid4()}_{filename}"
|
|
|
281 |
|
282 |
+
|
283 |
+
image_file.save(image_path)
|
284 |
elif base64_image:
|
285 |
+
# Save base64 image
|
286 |
try:
|
287 |
image_path = save_base64_image(base64_image)
|
288 |
+
# return jsonify({'image_path': image_path})
|
289 |
+
# image_path = (upload_image_to_hf(image_path, token))
|
290 |
+
|
291 |
+
print(f"Image saved at HF: {image_path}")
|
292 |
+
|
293 |
except Exception as e:
|
294 |
return jsonify({'error': f'Invalid base64 image data: {str(e)}'}), 400
|
295 |
else:
|
296 |
+
return jsonify({'error': 'Image is required (file or base64)'}), 400
|
297 |
|
298 |
+
# Load workflow configuration
|
299 |
current_dir = os.path.dirname(os.path.abspath(__file__))
|
300 |
+
workflow_path = os.path.join(current_dir, 'workflows/cogvideox_image_to_video_workflow_api.json')
|
301 |
+
with open(workflow_path, 'r', encoding='utf-8') as f:
|
302 |
+
workflow = json.load(f)
|
303 |
|
304 |
+
# Modify workflow with inputs
|
305 |
+
workflow["30"]["inputs"]["prompt"] = text_prompt
|
306 |
+
workflow["36"]["inputs"]["image"] = image_path
|
307 |
+
workflow["31"]["inputs"]["prompt"] = "Low quality, watermark, strange motion"
|
308 |
+
workflow["57"]["inputs"]["seed"] = random.randint(100000000000000, 999999999999999)
|
309 |
|
310 |
+
# WebSocket connection to queue and monitor workflow
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
311 |
ws = websocket.WebSocket()
|
312 |
+
try:
|
313 |
+
ws.connect(f"{ws_address}?clientId={client_id}&token={token}", header={"Authorization": f"Bearer {token}"})
|
314 |
+
except websocket.WebSocketException as e:
|
315 |
+
return jsonify({'error': f'WebSocket connection failed: {str(e)}'}), 500
|
316 |
|
317 |
+
try:
|
318 |
+
prompt_id = queue_prompt(workflow, token)
|
319 |
+
except ValueError as e:
|
320 |
+
return jsonify({'error': str(e)}), 400
|
321 |
+
|
322 |
+
# Wait for workflow execution to complete
|
323 |
while True:
|
324 |
+
message = json.loads(ws.recv())
|
325 |
+
if message.get('type') == 'executing' and message['data']['node'] is None and message['data']['prompt_id'] == prompt_id:
|
|
|
|
|
326 |
break
|
327 |
|
328 |
+
# Fetch video details
|
329 |
+
history = get_history(prompt_id, token).get(prompt_id, {})
|
330 |
+
video_data = None
|
331 |
+
for node_id, node_output in history.get('outputs', {}).items():
|
332 |
+
if 'videos' in node_output:
|
333 |
+
video = node_output['videos'][0]
|
334 |
+
video_data = get_video_data(video['filename'], video['subfolder'], token)
|
335 |
+
|
336 |
+
if not video_data:
|
337 |
+
return jsonify({'error': 'Failed to generate video'}), 500
|
338 |
+
|
339 |
+
# Save and return the generated video
|
340 |
+
local_video_path = f"/tmp/generated_video_{uuid.uuid4()}.mp4"
|
341 |
+
with open(local_video_path, 'wb') as f:
|
342 |
+
f.write(video_data)
|
343 |
+
|
344 |
return send_file(
|
345 |
+
io.BytesIO(video_data),
|
346 |
mimetype='video/mp4',
|
347 |
as_attachment=True,
|
348 |
download_name='generated_video.mp4'
|
349 |
)
|
350 |
|
351 |
+
|
352 |
if __name__ == '__main__':
|
353 |
+
app.run(host='0.0.0.0', port=7860, debug=True) # Removed 'debug=True'
|
requirements.txt
CHANGED
@@ -5,3 +5,4 @@ websocket-client
|
|
5 |
Pillow
|
6 |
uuid
|
7 |
gunicorn
|
|
|
|
5 |
Pillow
|
6 |
uuid
|
7 |
gunicorn
|
8 |
+
requests
|
workflows/cogvideox_image_to_video_workflow_api.json
CHANGED
@@ -54,7 +54,7 @@
|
|
54 |
},
|
55 |
"36": {
|
56 |
"inputs": {
|
57 |
-
"image": "Webimage-1-720x480.jpg",
|
58 |
"upload": "image"
|
59 |
},
|
60 |
"class_type": "LoadImage",
|
@@ -131,8 +131,8 @@
|
|
131 |
"steps": 50,
|
132 |
"cfg": 6,
|
133 |
"seed": 65334758276105,
|
134 |
-
"scheduler": "DPM",
|
135 |
-
"denoise_strength":
|
136 |
"pipeline": [
|
137 |
"1",
|
138 |
0
|
|
|
54 |
},
|
55 |
"36": {
|
56 |
"inputs": {
|
57 |
+
"image": "https://huggingface.co/spaces/gosign-de/comfyui-api/raw/main/images/Webimage-1-720x480.jpg",
|
58 |
"upload": "image"
|
59 |
},
|
60 |
"class_type": "LoadImage",
|
|
|
131 |
"steps": 50,
|
132 |
"cfg": 6,
|
133 |
"seed": 65334758276105,
|
134 |
+
"scheduler": "DPM++",
|
135 |
+
"denoise_strength": 1.0,
|
136 |
"pipeline": [
|
137 |
"1",
|
138 |
0
|